Contact Information

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W. Bartlett, PhD

Battelle Center for Mathematical MedicineAbigail Wexner Research Institute575 Children’s CrossroadColumbus, Ohio 43215 (map)

Learn more about Christopher W. Bartlett

Research

Lab(s)

Battelle Center for Mathematical Medicine

Bartlett Lab

My laboratory seeks to identify genetic factors for language impairments. As animal models of language development are of limited utility, we examine DNA from families segregating specific language impairment or autism as part of two separate but interacting projects. These projects are heavily interdisciplinary, utilizing a wide range of molecular and computational methods developed in-house and though close collaborations with experts in statistics and computer science. We hope that use of genetics will allow for identification of at-risk children to promote early intervention. Neurogenetics:My long-term goal is to understand the molecular neurobiology of human language. However, moreso than any other cognitive neuroscience topic, the neurobiology of language is quite resistant to use of animal models except in extremely circumscribed ways. My approach is to use “forward genetics” whereby we map language and related traits into the human genome in language impaired patient and family studies using a mix of statistics and genomics. This work entails three levels of basic research and experimentation that feed into the larger project. 1) Statistical genetics research where we develop the statistical methods necessary to directly model and thereby answer our specific research questions. This work involves both analytical and computational methods. 2) Molecular genetic methods and assay development to generate the raw data used in our analyses. 3) Studies of gene expression in the human brain using methods that are similar to those for mapping cognitive traits, but these research questions involve finding directly functional genomic elements that are active in the human brain, such polymorphisms are good candidates biomarkers and mediators of cognitive performance. Specific Language Impairment Research:Specific language impairment (SLI) is an idiopathic neurodevelopmental complex disorder consisting of clinically depressed language ability despite normal hearing, education and intelligence. Approximately 5-7 percentof school age children meet these criteria and represent the largest portion of children receiving special education services within the nation’s public school system costing on average an additional $2400/year per child while incurring less tax revenue due to lost educational opportunities. SLI is consistently heritable, defined either categorically or quantitatively (Bishop et al. 1995; Tomblin and Buckwalter 1998). To date, two genome-wide scans for SLI have been conducted (Bartlett et al. 2002; SLI_Consortium 2002). In a previous funding period we found compelling evidence for a susceptibility allele within our families selected for SLI on 13q21-22 (Bartlett et al. 2002) with a PPL of 53% (LOD=3.92). This finding was followed up with a replication PPL of 17 percent (LOD=2.62) (Bartlett et al. 2004); joint analysis of both datasets shows strong evidence for linkage to 13q21 with a PPL of 96.9 percent (LOD=7.86). We are executing a series of complementary approaches to assist in understanding the highly complex interrelationships between language and reading measures and how those relationships may underlie the SLI. To this end we are employing new multivariate approaches which are expected to 1) improve our understanding of how quantitative language and reading measures, some perhaps representing different etiologic mechanisms, relate to SLI as a diagnosis and 2) increase power to detect novel loci. Our strong linkage signal on 13q21 provides a solid foundation to perform a series of linkage/association analyses using uni- and multi-variate phenotypes including both categorical affection status and quantitative measures of language and related skills in order to dissect the multiple, heterogeneous, pathways to an SLI diagnosis. Behavioral and Genetic Biomarker Development for Autism and Related Disorders:The overall goal of this project is to advance the development of behavioral and genetic biomarkers for autism and related disorders. While it is clear that autism has a strong inherited genetic component, very large scale genetic studies that have relied only on a general diagnosis of autism (spectrum) disorders (or other information only on affected individuals) have had limited success in identifying risk alleles, leaving a critical issue for the field. Behavioral biomarkers, especially language ability, have been used with some success to increase power in gene mapping, but to date studies have focused on detailed behavioral assessments only of subjects with autism and not their family members, despite an extensive literature defining increased rates of related phenotypes in family members. We will use our existing family set with an extensive existing database of clinical and genetic data from all family members, where each family contains at least one proband with autism and at least one proband with a language deficit, to define biomarkers for risk. For Aim 1, Behavioral Biomarker Development, we will develop a set of behavioral biomarkers of genetic risk for autism and related disorders. We will analyze our extensive behavioral testing database to determine which measures have the strongest genetic effects and further examine latent class structures for both data reduction and to reduce measurement error. We will conduct follow-up assessments on a subset of study participants to determine longitudinal stability of selected biomarkers. For Aim 2, Behavioral Biomarker Validation, we will validate inherited components of the behavioral biomarkers through the use of genome-wide analysis. We will use analysis of quantitative and dichotomous behavioral biomarker data using a quasi-Bayesian posterior probability method to elucidate the genetic architecture of risk, providing evidence of the nature of the inherited genetic component. For Aim 3, Genetic Biomarker Identification, we will identify specific DNA variations associated with genetic risk for autism and related disorders. We will test both common and rare variants, SNPs and CNVs, from candidate genes within the regions identified in Aim 2 and evaluate additional variants from the literature as potential factors modulating a network of risk-determining genes. Identification of susceptibility genes through the approaches proposed could provide important insights into biological basis of this illness, which could result in the development of novel treatments.

Connect on LinkedIn Connect on Google Scholar

Publications

                  Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Common genetic risk factors in ASD and ADHD co-occurring families. Hum Genet. 2022 Oct 17;  

                


                  Wong A, Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders. Genes (Basel). 2022 Jul 26; 13: 

                


                  Bossenbroek J, Ueyama Y, McCallinhart PE, Bartlett CW, Ray WC, Trask AJ. Improvement of automated analysis of coronary Doppler echocardiograms. Sci Rep. 2022 May 6; 12: 7490.

                


                  Johnson TS, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Zaid MA, Huang X, Wang Y, Bartlett C, Zhang Y, Walker BA, Liu Y, Huang K, Zhang J. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease. Genome Med. 2022 Feb 1; 14: 11.

                


                  Pavlek LR, Vudatala S, Bartlett CW, Buhimschi IA, Buhimschi CS, Rogers LK. MiR-29b is associated with perinatal inflammation in extremely preterm infants. Pediatr Res. 2021 Mar; 89: 889-893.

                


                  Backes CH, Söderström F, Ågren J, Sindelar R, Bartlett CW, Rivera BK, Mitchell CC, Frey HA, Shepherd EG, Nelin LD, Normann E. Outcomes following a comprehensive versus a selective approach for infants born at 22 weeks of gestation. J Perinatol. 2019 Jan; 39: 39-47.

                


                  Laasonen M, Smolander S, Lahti-Nuuttila P, Leminen M, Lajunen HR, Heinonen K, Pesonen AK, Bailey TM, Pothos EM, Kujala T, Leppänen PHT, Bartlett CW, Geneid A, Lauronen L, Service E, Kunnari S, Arkkila E. Understanding developmental language disorder - the Helsinki longitudinal SLI study (HelSLI): a study protocol. BMC Psychol. 2018 May 21; 6: 24.

                


                  Swaminathan R, Huang Y, Astbury C, Fitzgerald-Butt S, Miller K, Cole J, Bartlett C, Lin S. Clinical exome sequencing reports: current informatics practice and future opportunities. J Am Med Inform Assoc. 2017 Nov 1; 24: 1184-1191.

                


                  Sheppard KW, Boone KM, Gracious B, Klebanoff MA, Rogers LK, Rausch J, Bartlett C, Coury DL, Keim SA. Effect of Omega-3 and -6 Supplementation on Language in Preterm Toddlers Exhibiting Autism Spectrum Disorder Symptoms. J Autism Dev Disord. 2017 Nov; 47: 3358-3369.

                


                  Bruni M, Flax JF, Buyske S, Shindhelm AD, Witton C, Brzustowicz LM, Bartlett CW. Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds. Behav Genet. 2017 Mar; 47: 193-201.

View More Publications

Biography

        Christopher W. Bartlett, PhD, is a principal investigator in the Battelle Center for Mathematical Medicine at the Research Institute at Nationwide Children’s Hospital and an Associate Professor of Pediatrics at the Ohio State University. Dr. Bartlett's NIH funded research program primarily focuses on the genetics of language impairments in families including isolated impairments or in conjunction with autism spectrum disorder.

See Christopher W. Bartlett’s Curriculum Vitae (CV)

Academic and Clinical Areas

Battelle Center for Mathematical Medicine

Faculty

Bartlett Lab

Principal Investigator

Primary Department

Battelle Center for Mathematical Medicine

Awards, Honors & Organizations

Bartlett et. al. in top ten best research papers on child development by Center of Excellence on Early Childhood Development, Université de Montréal, 2002 Graduate Fellowship for Academic Excellence, Johnson & Johnson, 1998 Inducted into Psy Chi, The National Honor Society for Psychology Students, 1998 - Present

Professional Experience

2014 - Present Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Associate Professor2014 - Present The Ohio State University College of Medicine, Associate Professor of Pediatrics2006 - 2014 The Ohio State University College of Medicine, Assistant Professor of Pediatrics2006 - 2014 Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Assistant Professor2006 - 2007 Center for Quantitative and Computational Biology, The Research Institute at Nationwide Children’s Hospital, Assistant Professor

Contact Information

Battelle Center for Mathematical Medicine

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W Bartlett

                    Abigail Wexner Research Institute575 Children's CrossroadColumbus, Ohio 43215 (map)

Contact Information

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W. Bartlett, PhD

Battelle Center for Mathematical MedicineAbigail Wexner Research Institute575 Children’s CrossroadColumbus, Ohio 43215 (map)

Learn more about Christopher W. Bartlett

Research

Lab(s)

Battelle Center for Mathematical Medicine

Bartlett Lab

My laboratory seeks to identify genetic factors for language impairments. As animal models of language development are of limited utility, we examine DNA from families segregating specific language impairment or autism as part of two separate but interacting projects. These projects are heavily interdisciplinary, utilizing a wide range of molecular and computational methods developed in-house and though close collaborations with experts in statistics and computer science. We hope that use of genetics will allow for identification of at-risk children to promote early intervention. Neurogenetics:My long-term goal is to understand the molecular neurobiology of human language. However, moreso than any other cognitive neuroscience topic, the neurobiology of language is quite resistant to use of animal models except in extremely circumscribed ways. My approach is to use “forward genetics” whereby we map language and related traits into the human genome in language impaired patient and family studies using a mix of statistics and genomics. This work entails three levels of basic research and experimentation that feed into the larger project. 1) Statistical genetics research where we develop the statistical methods necessary to directly model and thereby answer our specific research questions. This work involves both analytical and computational methods. 2) Molecular genetic methods and assay development to generate the raw data used in our analyses. 3) Studies of gene expression in the human brain using methods that are similar to those for mapping cognitive traits, but these research questions involve finding directly functional genomic elements that are active in the human brain, such polymorphisms are good candidates biomarkers and mediators of cognitive performance. Specific Language Impairment Research:Specific language impairment (SLI) is an idiopathic neurodevelopmental complex disorder consisting of clinically depressed language ability despite normal hearing, education and intelligence. Approximately 5-7 percentof school age children meet these criteria and represent the largest portion of children receiving special education services within the nation’s public school system costing on average an additional $2400/year per child while incurring less tax revenue due to lost educational opportunities. SLI is consistently heritable, defined either categorically or quantitatively (Bishop et al. 1995; Tomblin and Buckwalter 1998). To date, two genome-wide scans for SLI have been conducted (Bartlett et al. 2002; SLI_Consortium 2002). In a previous funding period we found compelling evidence for a susceptibility allele within our families selected for SLI on 13q21-22 (Bartlett et al. 2002) with a PPL of 53% (LOD=3.92). This finding was followed up with a replication PPL of 17 percent (LOD=2.62) (Bartlett et al. 2004); joint analysis of both datasets shows strong evidence for linkage to 13q21 with a PPL of 96.9 percent (LOD=7.86). We are executing a series of complementary approaches to assist in understanding the highly complex interrelationships between language and reading measures and how those relationships may underlie the SLI. To this end we are employing new multivariate approaches which are expected to 1) improve our understanding of how quantitative language and reading measures, some perhaps representing different etiologic mechanisms, relate to SLI as a diagnosis and 2) increase power to detect novel loci. Our strong linkage signal on 13q21 provides a solid foundation to perform a series of linkage/association analyses using uni- and multi-variate phenotypes including both categorical affection status and quantitative measures of language and related skills in order to dissect the multiple, heterogeneous, pathways to an SLI diagnosis. Behavioral and Genetic Biomarker Development for Autism and Related Disorders:The overall goal of this project is to advance the development of behavioral and genetic biomarkers for autism and related disorders. While it is clear that autism has a strong inherited genetic component, very large scale genetic studies that have relied only on a general diagnosis of autism (spectrum) disorders (or other information only on affected individuals) have had limited success in identifying risk alleles, leaving a critical issue for the field. Behavioral biomarkers, especially language ability, have been used with some success to increase power in gene mapping, but to date studies have focused on detailed behavioral assessments only of subjects with autism and not their family members, despite an extensive literature defining increased rates of related phenotypes in family members. We will use our existing family set with an extensive existing database of clinical and genetic data from all family members, where each family contains at least one proband with autism and at least one proband with a language deficit, to define biomarkers for risk. For Aim 1, Behavioral Biomarker Development, we will develop a set of behavioral biomarkers of genetic risk for autism and related disorders. We will analyze our extensive behavioral testing database to determine which measures have the strongest genetic effects and further examine latent class structures for both data reduction and to reduce measurement error. We will conduct follow-up assessments on a subset of study participants to determine longitudinal stability of selected biomarkers. For Aim 2, Behavioral Biomarker Validation, we will validate inherited components of the behavioral biomarkers through the use of genome-wide analysis. We will use analysis of quantitative and dichotomous behavioral biomarker data using a quasi-Bayesian posterior probability method to elucidate the genetic architecture of risk, providing evidence of the nature of the inherited genetic component. For Aim 3, Genetic Biomarker Identification, we will identify specific DNA variations associated with genetic risk for autism and related disorders. We will test both common and rare variants, SNPs and CNVs, from candidate genes within the regions identified in Aim 2 and evaluate additional variants from the literature as potential factors modulating a network of risk-determining genes. Identification of susceptibility genes through the approaches proposed could provide important insights into biological basis of this illness, which could result in the development of novel treatments.

Connect on LinkedIn Connect on Google Scholar

Publications

                  Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Common genetic risk factors in ASD and ADHD co-occurring families. Hum Genet. 2022 Oct 17;  

                


                  Wong A, Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders. Genes (Basel). 2022 Jul 26; 13: 

                


                  Bossenbroek J, Ueyama Y, McCallinhart PE, Bartlett CW, Ray WC, Trask AJ. Improvement of automated analysis of coronary Doppler echocardiograms. Sci Rep. 2022 May 6; 12: 7490.

                


                  Johnson TS, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Zaid MA, Huang X, Wang Y, Bartlett C, Zhang Y, Walker BA, Liu Y, Huang K, Zhang J. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease. Genome Med. 2022 Feb 1; 14: 11.

                


                  Pavlek LR, Vudatala S, Bartlett CW, Buhimschi IA, Buhimschi CS, Rogers LK. MiR-29b is associated with perinatal inflammation in extremely preterm infants. Pediatr Res. 2021 Mar; 89: 889-893.

                


                  Backes CH, Söderström F, Ågren J, Sindelar R, Bartlett CW, Rivera BK, Mitchell CC, Frey HA, Shepherd EG, Nelin LD, Normann E. Outcomes following a comprehensive versus a selective approach for infants born at 22 weeks of gestation. J Perinatol. 2019 Jan; 39: 39-47.

                


                  Laasonen M, Smolander S, Lahti-Nuuttila P, Leminen M, Lajunen HR, Heinonen K, Pesonen AK, Bailey TM, Pothos EM, Kujala T, Leppänen PHT, Bartlett CW, Geneid A, Lauronen L, Service E, Kunnari S, Arkkila E. Understanding developmental language disorder - the Helsinki longitudinal SLI study (HelSLI): a study protocol. BMC Psychol. 2018 May 21; 6: 24.

                


                  Swaminathan R, Huang Y, Astbury C, Fitzgerald-Butt S, Miller K, Cole J, Bartlett C, Lin S. Clinical exome sequencing reports: current informatics practice and future opportunities. J Am Med Inform Assoc. 2017 Nov 1; 24: 1184-1191.

                


                  Sheppard KW, Boone KM, Gracious B, Klebanoff MA, Rogers LK, Rausch J, Bartlett C, Coury DL, Keim SA. Effect of Omega-3 and -6 Supplementation on Language in Preterm Toddlers Exhibiting Autism Spectrum Disorder Symptoms. J Autism Dev Disord. 2017 Nov; 47: 3358-3369.

                


                  Bruni M, Flax JF, Buyske S, Shindhelm AD, Witton C, Brzustowicz LM, Bartlett CW. Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds. Behav Genet. 2017 Mar; 47: 193-201.

View More Publications

Biography

        Christopher W. Bartlett, PhD, is a principal investigator in the Battelle Center for Mathematical Medicine at the Research Institute at Nationwide Children’s Hospital and an Associate Professor of Pediatrics at the Ohio State University. Dr. Bartlett's NIH funded research program primarily focuses on the genetics of language impairments in families including isolated impairments or in conjunction with autism spectrum disorder.

See Christopher W. Bartlett’s Curriculum Vitae (CV)

Academic and Clinical Areas

Battelle Center for Mathematical Medicine

Faculty

Bartlett Lab

Principal Investigator

Primary Department

Battelle Center for Mathematical Medicine

Awards, Honors & Organizations

Bartlett et. al. in top ten best research papers on child development by Center of Excellence on Early Childhood Development, Université de Montréal, 2002 Graduate Fellowship for Academic Excellence, Johnson & Johnson, 1998 Inducted into Psy Chi, The National Honor Society for Psychology Students, 1998 - Present

Professional Experience

2014 - Present Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Associate Professor2014 - Present The Ohio State University College of Medicine, Associate Professor of Pediatrics2006 - 2014 The Ohio State University College of Medicine, Assistant Professor of Pediatrics2006 - 2014 Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Assistant Professor2006 - 2007 Center for Quantitative and Computational Biology, The Research Institute at Nationwide Children’s Hospital, Assistant Professor

Contact Information

Battelle Center for Mathematical Medicine

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W Bartlett

                    Abigail Wexner Research Institute575 Children's CrossroadColumbus, Ohio 43215 (map)

Contact Information

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W. Bartlett, PhD

Battelle Center for Mathematical MedicineAbigail Wexner Research Institute575 Children’s CrossroadColumbus, Ohio 43215 (map)

Learn more about Christopher W. Bartlett

Contact Information

  • Call us at:
  • (614)355-5625
  • Fax us at:
  • (614)355-2728
  • Email Christopher W. Bartlett, PhD
  • Battelle Center for Mathematical MedicineAbigail Wexner Research Institute575 Children’s CrossroadColumbus, Ohio 43215 (map)

Learn more about Christopher W. Bartlett

Research

Lab(s)

Battelle Center for Mathematical Medicine

Bartlett Lab

My laboratory seeks to identify genetic factors for language impairments. As animal models of language development are of limited utility, we examine DNA from families segregating specific language impairment or autism as part of two separate but interacting projects. These projects are heavily interdisciplinary, utilizing a wide range of molecular and computational methods developed in-house and though close collaborations with experts in statistics and computer science. We hope that use of genetics will allow for identification of at-risk children to promote early intervention. Neurogenetics:My long-term goal is to understand the molecular neurobiology of human language. However, moreso than any other cognitive neuroscience topic, the neurobiology of language is quite resistant to use of animal models except in extremely circumscribed ways. My approach is to use “forward genetics” whereby we map language and related traits into the human genome in language impaired patient and family studies using a mix of statistics and genomics. This work entails three levels of basic research and experimentation that feed into the larger project. 1) Statistical genetics research where we develop the statistical methods necessary to directly model and thereby answer our specific research questions. This work involves both analytical and computational methods. 2) Molecular genetic methods and assay development to generate the raw data used in our analyses. 3) Studies of gene expression in the human brain using methods that are similar to those for mapping cognitive traits, but these research questions involve finding directly functional genomic elements that are active in the human brain, such polymorphisms are good candidates biomarkers and mediators of cognitive performance. Specific Language Impairment Research:Specific language impairment (SLI) is an idiopathic neurodevelopmental complex disorder consisting of clinically depressed language ability despite normal hearing, education and intelligence. Approximately 5-7 percentof school age children meet these criteria and represent the largest portion of children receiving special education services within the nation’s public school system costing on average an additional $2400/year per child while incurring less tax revenue due to lost educational opportunities. SLI is consistently heritable, defined either categorically or quantitatively (Bishop et al. 1995; Tomblin and Buckwalter 1998). To date, two genome-wide scans for SLI have been conducted (Bartlett et al. 2002; SLI_Consortium 2002). In a previous funding period we found compelling evidence for a susceptibility allele within our families selected for SLI on 13q21-22 (Bartlett et al. 2002) with a PPL of 53% (LOD=3.92). This finding was followed up with a replication PPL of 17 percent (LOD=2.62) (Bartlett et al. 2004); joint analysis of both datasets shows strong evidence for linkage to 13q21 with a PPL of 96.9 percent (LOD=7.86). We are executing a series of complementary approaches to assist in understanding the highly complex interrelationships between language and reading measures and how those relationships may underlie the SLI. To this end we are employing new multivariate approaches which are expected to 1) improve our understanding of how quantitative language and reading measures, some perhaps representing different etiologic mechanisms, relate to SLI as a diagnosis and 2) increase power to detect novel loci. Our strong linkage signal on 13q21 provides a solid foundation to perform a series of linkage/association analyses using uni- and multi-variate phenotypes including both categorical affection status and quantitative measures of language and related skills in order to dissect the multiple, heterogeneous, pathways to an SLI diagnosis. Behavioral and Genetic Biomarker Development for Autism and Related Disorders:The overall goal of this project is to advance the development of behavioral and genetic biomarkers for autism and related disorders. While it is clear that autism has a strong inherited genetic component, very large scale genetic studies that have relied only on a general diagnosis of autism (spectrum) disorders (or other information only on affected individuals) have had limited success in identifying risk alleles, leaving a critical issue for the field. Behavioral biomarkers, especially language ability, have been used with some success to increase power in gene mapping, but to date studies have focused on detailed behavioral assessments only of subjects with autism and not their family members, despite an extensive literature defining increased rates of related phenotypes in family members. We will use our existing family set with an extensive existing database of clinical and genetic data from all family members, where each family contains at least one proband with autism and at least one proband with a language deficit, to define biomarkers for risk. For Aim 1, Behavioral Biomarker Development, we will develop a set of behavioral biomarkers of genetic risk for autism and related disorders. We will analyze our extensive behavioral testing database to determine which measures have the strongest genetic effects and further examine latent class structures for both data reduction and to reduce measurement error. We will conduct follow-up assessments on a subset of study participants to determine longitudinal stability of selected biomarkers. For Aim 2, Behavioral Biomarker Validation, we will validate inherited components of the behavioral biomarkers through the use of genome-wide analysis. We will use analysis of quantitative and dichotomous behavioral biomarker data using a quasi-Bayesian posterior probability method to elucidate the genetic architecture of risk, providing evidence of the nature of the inherited genetic component. For Aim 3, Genetic Biomarker Identification, we will identify specific DNA variations associated with genetic risk for autism and related disorders. We will test both common and rare variants, SNPs and CNVs, from candidate genes within the regions identified in Aim 2 and evaluate additional variants from the literature as potential factors modulating a network of risk-determining genes. Identification of susceptibility genes through the approaches proposed could provide important insights into biological basis of this illness, which could result in the development of novel treatments.

Connect on LinkedIn Connect on Google Scholar

Publications

                  Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Common genetic risk factors in ASD and ADHD co-occurring families. Hum Genet. 2022 Oct 17;  

                


                  Wong A, Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders. Genes (Basel). 2022 Jul 26; 13: 

                


                  Bossenbroek J, Ueyama Y, McCallinhart PE, Bartlett CW, Ray WC, Trask AJ. Improvement of automated analysis of coronary Doppler echocardiograms. Sci Rep. 2022 May 6; 12: 7490.

                


                  Johnson TS, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Zaid MA, Huang X, Wang Y, Bartlett C, Zhang Y, Walker BA, Liu Y, Huang K, Zhang J. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease. Genome Med. 2022 Feb 1; 14: 11.

                


                  Pavlek LR, Vudatala S, Bartlett CW, Buhimschi IA, Buhimschi CS, Rogers LK. MiR-29b is associated with perinatal inflammation in extremely preterm infants. Pediatr Res. 2021 Mar; 89: 889-893.

                


                  Backes CH, Söderström F, Ågren J, Sindelar R, Bartlett CW, Rivera BK, Mitchell CC, Frey HA, Shepherd EG, Nelin LD, Normann E. Outcomes following a comprehensive versus a selective approach for infants born at 22 weeks of gestation. J Perinatol. 2019 Jan; 39: 39-47.

                


                  Laasonen M, Smolander S, Lahti-Nuuttila P, Leminen M, Lajunen HR, Heinonen K, Pesonen AK, Bailey TM, Pothos EM, Kujala T, Leppänen PHT, Bartlett CW, Geneid A, Lauronen L, Service E, Kunnari S, Arkkila E. Understanding developmental language disorder - the Helsinki longitudinal SLI study (HelSLI): a study protocol. BMC Psychol. 2018 May 21; 6: 24.

                


                  Swaminathan R, Huang Y, Astbury C, Fitzgerald-Butt S, Miller K, Cole J, Bartlett C, Lin S. Clinical exome sequencing reports: current informatics practice and future opportunities. J Am Med Inform Assoc. 2017 Nov 1; 24: 1184-1191.

                


                  Sheppard KW, Boone KM, Gracious B, Klebanoff MA, Rogers LK, Rausch J, Bartlett C, Coury DL, Keim SA. Effect of Omega-3 and -6 Supplementation on Language in Preterm Toddlers Exhibiting Autism Spectrum Disorder Symptoms. J Autism Dev Disord. 2017 Nov; 47: 3358-3369.

                


                  Bruni M, Flax JF, Buyske S, Shindhelm AD, Witton C, Brzustowicz LM, Bartlett CW. Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds. Behav Genet. 2017 Mar; 47: 193-201.

View More Publications

Research

Lab(s)

Battelle Center for Mathematical Medicine

Bartlett Lab

My laboratory seeks to identify genetic factors for language impairments. As animal models of language development are of limited utility, we examine DNA from families segregating specific language impairment or autism as part of two separate but interacting projects. These projects are heavily interdisciplinary, utilizing a wide range of molecular and computational methods developed in-house and though close collaborations with experts in statistics and computer science. We hope that use of genetics will allow for identification of at-risk children to promote early intervention. Neurogenetics:My long-term goal is to understand the molecular neurobiology of human language. However, moreso than any other cognitive neuroscience topic, the neurobiology of language is quite resistant to use of animal models except in extremely circumscribed ways. My approach is to use “forward genetics” whereby we map language and related traits into the human genome in language impaired patient and family studies using a mix of statistics and genomics. This work entails three levels of basic research and experimentation that feed into the larger project. 1) Statistical genetics research where we develop the statistical methods necessary to directly model and thereby answer our specific research questions. This work involves both analytical and computational methods. 2) Molecular genetic methods and assay development to generate the raw data used in our analyses. 3) Studies of gene expression in the human brain using methods that are similar to those for mapping cognitive traits, but these research questions involve finding directly functional genomic elements that are active in the human brain, such polymorphisms are good candidates biomarkers and mediators of cognitive performance. Specific Language Impairment Research:Specific language impairment (SLI) is an idiopathic neurodevelopmental complex disorder consisting of clinically depressed language ability despite normal hearing, education and intelligence. Approximately 5-7 percentof school age children meet these criteria and represent the largest portion of children receiving special education services within the nation’s public school system costing on average an additional $2400/year per child while incurring less tax revenue due to lost educational opportunities. SLI is consistently heritable, defined either categorically or quantitatively (Bishop et al. 1995; Tomblin and Buckwalter 1998). To date, two genome-wide scans for SLI have been conducted (Bartlett et al. 2002; SLI_Consortium 2002). In a previous funding period we found compelling evidence for a susceptibility allele within our families selected for SLI on 13q21-22 (Bartlett et al. 2002) with a PPL of 53% (LOD=3.92). This finding was followed up with a replication PPL of 17 percent (LOD=2.62) (Bartlett et al. 2004); joint analysis of both datasets shows strong evidence for linkage to 13q21 with a PPL of 96.9 percent (LOD=7.86). We are executing a series of complementary approaches to assist in understanding the highly complex interrelationships between language and reading measures and how those relationships may underlie the SLI. To this end we are employing new multivariate approaches which are expected to 1) improve our understanding of how quantitative language and reading measures, some perhaps representing different etiologic mechanisms, relate to SLI as a diagnosis and 2) increase power to detect novel loci. Our strong linkage signal on 13q21 provides a solid foundation to perform a series of linkage/association analyses using uni- and multi-variate phenotypes including both categorical affection status and quantitative measures of language and related skills in order to dissect the multiple, heterogeneous, pathways to an SLI diagnosis. Behavioral and Genetic Biomarker Development for Autism and Related Disorders:The overall goal of this project is to advance the development of behavioral and genetic biomarkers for autism and related disorders. While it is clear that autism has a strong inherited genetic component, very large scale genetic studies that have relied only on a general diagnosis of autism (spectrum) disorders (or other information only on affected individuals) have had limited success in identifying risk alleles, leaving a critical issue for the field. Behavioral biomarkers, especially language ability, have been used with some success to increase power in gene mapping, but to date studies have focused on detailed behavioral assessments only of subjects with autism and not their family members, despite an extensive literature defining increased rates of related phenotypes in family members. We will use our existing family set with an extensive existing database of clinical and genetic data from all family members, where each family contains at least one proband with autism and at least one proband with a language deficit, to define biomarkers for risk. For Aim 1, Behavioral Biomarker Development, we will develop a set of behavioral biomarkers of genetic risk for autism and related disorders. We will analyze our extensive behavioral testing database to determine which measures have the strongest genetic effects and further examine latent class structures for both data reduction and to reduce measurement error. We will conduct follow-up assessments on a subset of study participants to determine longitudinal stability of selected biomarkers. For Aim 2, Behavioral Biomarker Validation, we will validate inherited components of the behavioral biomarkers through the use of genome-wide analysis. We will use analysis of quantitative and dichotomous behavioral biomarker data using a quasi-Bayesian posterior probability method to elucidate the genetic architecture of risk, providing evidence of the nature of the inherited genetic component. For Aim 3, Genetic Biomarker Identification, we will identify specific DNA variations associated with genetic risk for autism and related disorders. We will test both common and rare variants, SNPs and CNVs, from candidate genes within the regions identified in Aim 2 and evaluate additional variants from the literature as potential factors modulating a network of risk-determining genes. Identification of susceptibility genes through the approaches proposed could provide important insights into biological basis of this illness, which could result in the development of novel treatments.

Connect on LinkedIn Connect on Google Scholar

Publications

                  Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Common genetic risk factors in ASD and ADHD co-occurring families. Hum Genet. 2022 Oct 17;  

                


                  Wong A, Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders. Genes (Basel). 2022 Jul 26; 13: 

                


                  Bossenbroek J, Ueyama Y, McCallinhart PE, Bartlett CW, Ray WC, Trask AJ. Improvement of automated analysis of coronary Doppler echocardiograms. Sci Rep. 2022 May 6; 12: 7490.

                


                  Johnson TS, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Zaid MA, Huang X, Wang Y, Bartlett C, Zhang Y, Walker BA, Liu Y, Huang K, Zhang J. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease. Genome Med. 2022 Feb 1; 14: 11.

                


                  Pavlek LR, Vudatala S, Bartlett CW, Buhimschi IA, Buhimschi CS, Rogers LK. MiR-29b is associated with perinatal inflammation in extremely preterm infants. Pediatr Res. 2021 Mar; 89: 889-893.

                


                  Backes CH, Söderström F, Ågren J, Sindelar R, Bartlett CW, Rivera BK, Mitchell CC, Frey HA, Shepherd EG, Nelin LD, Normann E. Outcomes following a comprehensive versus a selective approach for infants born at 22 weeks of gestation. J Perinatol. 2019 Jan; 39: 39-47.

                


                  Laasonen M, Smolander S, Lahti-Nuuttila P, Leminen M, Lajunen HR, Heinonen K, Pesonen AK, Bailey TM, Pothos EM, Kujala T, Leppänen PHT, Bartlett CW, Geneid A, Lauronen L, Service E, Kunnari S, Arkkila E. Understanding developmental language disorder - the Helsinki longitudinal SLI study (HelSLI): a study protocol. BMC Psychol. 2018 May 21; 6: 24.

                


                  Swaminathan R, Huang Y, Astbury C, Fitzgerald-Butt S, Miller K, Cole J, Bartlett C, Lin S. Clinical exome sequencing reports: current informatics practice and future opportunities. J Am Med Inform Assoc. 2017 Nov 1; 24: 1184-1191.

                


                  Sheppard KW, Boone KM, Gracious B, Klebanoff MA, Rogers LK, Rausch J, Bartlett C, Coury DL, Keim SA. Effect of Omega-3 and -6 Supplementation on Language in Preterm Toddlers Exhibiting Autism Spectrum Disorder Symptoms. J Autism Dev Disord. 2017 Nov; 47: 3358-3369.

                


                  Bruni M, Flax JF, Buyske S, Shindhelm AD, Witton C, Brzustowicz LM, Bartlett CW. Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds. Behav Genet. 2017 Mar; 47: 193-201.

View More Publications

Research

Lab(s)

Battelle Center for Mathematical Medicine

Bartlett Lab

My laboratory seeks to identify genetic factors for language impairments. As animal models of language development are of limited utility, we examine DNA from families segregating specific language impairment or autism as part of two separate but interacting projects. These projects are heavily interdisciplinary, utilizing a wide range of molecular and computational methods developed in-house and though close collaborations with experts in statistics and computer science. We hope that use of genetics will allow for identification of at-risk children to promote early intervention. Neurogenetics:My long-term goal is to understand the molecular neurobiology of human language. However, moreso than any other cognitive neuroscience topic, the neurobiology of language is quite resistant to use of animal models except in extremely circumscribed ways. My approach is to use “forward genetics” whereby we map language and related traits into the human genome in language impaired patient and family studies using a mix of statistics and genomics. This work entails three levels of basic research and experimentation that feed into the larger project. 1) Statistical genetics research where we develop the statistical methods necessary to directly model and thereby answer our specific research questions. This work involves both analytical and computational methods. 2) Molecular genetic methods and assay development to generate the raw data used in our analyses. 3) Studies of gene expression in the human brain using methods that are similar to those for mapping cognitive traits, but these research questions involve finding directly functional genomic elements that are active in the human brain, such polymorphisms are good candidates biomarkers and mediators of cognitive performance. Specific Language Impairment Research:Specific language impairment (SLI) is an idiopathic neurodevelopmental complex disorder consisting of clinically depressed language ability despite normal hearing, education and intelligence. Approximately 5-7 percentof school age children meet these criteria and represent the largest portion of children receiving special education services within the nation’s public school system costing on average an additional $2400/year per child while incurring less tax revenue due to lost educational opportunities. SLI is consistently heritable, defined either categorically or quantitatively (Bishop et al. 1995; Tomblin and Buckwalter 1998). To date, two genome-wide scans for SLI have been conducted (Bartlett et al. 2002; SLI_Consortium 2002). In a previous funding period we found compelling evidence for a susceptibility allele within our families selected for SLI on 13q21-22 (Bartlett et al. 2002) with a PPL of 53% (LOD=3.92). This finding was followed up with a replication PPL of 17 percent (LOD=2.62) (Bartlett et al. 2004); joint analysis of both datasets shows strong evidence for linkage to 13q21 with a PPL of 96.9 percent (LOD=7.86). We are executing a series of complementary approaches to assist in understanding the highly complex interrelationships between language and reading measures and how those relationships may underlie the SLI. To this end we are employing new multivariate approaches which are expected to 1) improve our understanding of how quantitative language and reading measures, some perhaps representing different etiologic mechanisms, relate to SLI as a diagnosis and 2) increase power to detect novel loci. Our strong linkage signal on 13q21 provides a solid foundation to perform a series of linkage/association analyses using uni- and multi-variate phenotypes including both categorical affection status and quantitative measures of language and related skills in order to dissect the multiple, heterogeneous, pathways to an SLI diagnosis. Behavioral and Genetic Biomarker Development for Autism and Related Disorders:The overall goal of this project is to advance the development of behavioral and genetic biomarkers for autism and related disorders. While it is clear that autism has a strong inherited genetic component, very large scale genetic studies that have relied only on a general diagnosis of autism (spectrum) disorders (or other information only on affected individuals) have had limited success in identifying risk alleles, leaving a critical issue for the field. Behavioral biomarkers, especially language ability, have been used with some success to increase power in gene mapping, but to date studies have focused on detailed behavioral assessments only of subjects with autism and not their family members, despite an extensive literature defining increased rates of related phenotypes in family members. We will use our existing family set with an extensive existing database of clinical and genetic data from all family members, where each family contains at least one proband with autism and at least one proband with a language deficit, to define biomarkers for risk. For Aim 1, Behavioral Biomarker Development, we will develop a set of behavioral biomarkers of genetic risk for autism and related disorders. We will analyze our extensive behavioral testing database to determine which measures have the strongest genetic effects and further examine latent class structures for both data reduction and to reduce measurement error. We will conduct follow-up assessments on a subset of study participants to determine longitudinal stability of selected biomarkers. For Aim 2, Behavioral Biomarker Validation, we will validate inherited components of the behavioral biomarkers through the use of genome-wide analysis. We will use analysis of quantitative and dichotomous behavioral biomarker data using a quasi-Bayesian posterior probability method to elucidate the genetic architecture of risk, providing evidence of the nature of the inherited genetic component. For Aim 3, Genetic Biomarker Identification, we will identify specific DNA variations associated with genetic risk for autism and related disorders. We will test both common and rare variants, SNPs and CNVs, from candidate genes within the regions identified in Aim 2 and evaluate additional variants from the literature as potential factors modulating a network of risk-determining genes. Identification of susceptibility genes through the approaches proposed could provide important insights into biological basis of this illness, which could result in the development of novel treatments.

Connect on LinkedIn Connect on Google Scholar

Publications

                  Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Common genetic risk factors in ASD and ADHD co-occurring families. Hum Genet. 2022 Oct 17;  

                


                  Wong A, Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders. Genes (Basel). 2022 Jul 26; 13: 

                


                  Bossenbroek J, Ueyama Y, McCallinhart PE, Bartlett CW, Ray WC, Trask AJ. Improvement of automated analysis of coronary Doppler echocardiograms. Sci Rep. 2022 May 6; 12: 7490.

                


                  Johnson TS, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Zaid MA, Huang X, Wang Y, Bartlett C, Zhang Y, Walker BA, Liu Y, Huang K, Zhang J. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease. Genome Med. 2022 Feb 1; 14: 11.

                


                  Pavlek LR, Vudatala S, Bartlett CW, Buhimschi IA, Buhimschi CS, Rogers LK. MiR-29b is associated with perinatal inflammation in extremely preterm infants. Pediatr Res. 2021 Mar; 89: 889-893.

                


                  Backes CH, Söderström F, Ågren J, Sindelar R, Bartlett CW, Rivera BK, Mitchell CC, Frey HA, Shepherd EG, Nelin LD, Normann E. Outcomes following a comprehensive versus a selective approach for infants born at 22 weeks of gestation. J Perinatol. 2019 Jan; 39: 39-47.

                


                  Laasonen M, Smolander S, Lahti-Nuuttila P, Leminen M, Lajunen HR, Heinonen K, Pesonen AK, Bailey TM, Pothos EM, Kujala T, Leppänen PHT, Bartlett CW, Geneid A, Lauronen L, Service E, Kunnari S, Arkkila E. Understanding developmental language disorder - the Helsinki longitudinal SLI study (HelSLI): a study protocol. BMC Psychol. 2018 May 21; 6: 24.

                


                  Swaminathan R, Huang Y, Astbury C, Fitzgerald-Butt S, Miller K, Cole J, Bartlett C, Lin S. Clinical exome sequencing reports: current informatics practice and future opportunities. J Am Med Inform Assoc. 2017 Nov 1; 24: 1184-1191.

                


                  Sheppard KW, Boone KM, Gracious B, Klebanoff MA, Rogers LK, Rausch J, Bartlett C, Coury DL, Keim SA. Effect of Omega-3 and -6 Supplementation on Language in Preterm Toddlers Exhibiting Autism Spectrum Disorder Symptoms. J Autism Dev Disord. 2017 Nov; 47: 3358-3369.

                


                  Bruni M, Flax JF, Buyske S, Shindhelm AD, Witton C, Brzustowicz LM, Bartlett CW. Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds. Behav Genet. 2017 Mar; 47: 193-201.

View More Publications

Lab(s)

Battelle Center for Mathematical Medicine

Bartlett Lab

My laboratory seeks to identify genetic factors for language impairments. As animal models of language development are of limited utility, we examine DNA from families segregating specific language impairment or autism as part of two separate but interacting projects. These projects are heavily interdisciplinary, utilizing a wide range of molecular and computational methods developed in-house and though close collaborations with experts in statistics and computer science. We hope that use of genetics will allow for identification of at-risk children to promote early intervention. Neurogenetics:My long-term goal is to understand the molecular neurobiology of human language. However, moreso than any other cognitive neuroscience topic, the neurobiology of language is quite resistant to use of animal models except in extremely circumscribed ways. My approach is to use “forward genetics” whereby we map language and related traits into the human genome in language impaired patient and family studies using a mix of statistics and genomics. This work entails three levels of basic research and experimentation that feed into the larger project. 1) Statistical genetics research where we develop the statistical methods necessary to directly model and thereby answer our specific research questions. This work involves both analytical and computational methods. 2) Molecular genetic methods and assay development to generate the raw data used in our analyses. 3) Studies of gene expression in the human brain using methods that are similar to those for mapping cognitive traits, but these research questions involve finding directly functional genomic elements that are active in the human brain, such polymorphisms are good candidates biomarkers and mediators of cognitive performance. Specific Language Impairment Research:Specific language impairment (SLI) is an idiopathic neurodevelopmental complex disorder consisting of clinically depressed language ability despite normal hearing, education and intelligence. Approximately 5-7 percentof school age children meet these criteria and represent the largest portion of children receiving special education services within the nation’s public school system costing on average an additional $2400/year per child while incurring less tax revenue due to lost educational opportunities. SLI is consistently heritable, defined either categorically or quantitatively (Bishop et al. 1995; Tomblin and Buckwalter 1998). To date, two genome-wide scans for SLI have been conducted (Bartlett et al. 2002; SLI_Consortium 2002). In a previous funding period we found compelling evidence for a susceptibility allele within our families selected for SLI on 13q21-22 (Bartlett et al. 2002) with a PPL of 53% (LOD=3.92). This finding was followed up with a replication PPL of 17 percent (LOD=2.62) (Bartlett et al. 2004); joint analysis of both datasets shows strong evidence for linkage to 13q21 with a PPL of 96.9 percent (LOD=7.86). We are executing a series of complementary approaches to assist in understanding the highly complex interrelationships between language and reading measures and how those relationships may underlie the SLI. To this end we are employing new multivariate approaches which are expected to 1) improve our understanding of how quantitative language and reading measures, some perhaps representing different etiologic mechanisms, relate to SLI as a diagnosis and 2) increase power to detect novel loci. Our strong linkage signal on 13q21 provides a solid foundation to perform a series of linkage/association analyses using uni- and multi-variate phenotypes including both categorical affection status and quantitative measures of language and related skills in order to dissect the multiple, heterogeneous, pathways to an SLI diagnosis. Behavioral and Genetic Biomarker Development for Autism and Related Disorders:The overall goal of this project is to advance the development of behavioral and genetic biomarkers for autism and related disorders. While it is clear that autism has a strong inherited genetic component, very large scale genetic studies that have relied only on a general diagnosis of autism (spectrum) disorders (or other information only on affected individuals) have had limited success in identifying risk alleles, leaving a critical issue for the field. Behavioral biomarkers, especially language ability, have been used with some success to increase power in gene mapping, but to date studies have focused on detailed behavioral assessments only of subjects with autism and not their family members, despite an extensive literature defining increased rates of related phenotypes in family members. We will use our existing family set with an extensive existing database of clinical and genetic data from all family members, where each family contains at least one proband with autism and at least one proband with a language deficit, to define biomarkers for risk. For Aim 1, Behavioral Biomarker Development, we will develop a set of behavioral biomarkers of genetic risk for autism and related disorders. We will analyze our extensive behavioral testing database to determine which measures have the strongest genetic effects and further examine latent class structures for both data reduction and to reduce measurement error. We will conduct follow-up assessments on a subset of study participants to determine longitudinal stability of selected biomarkers. For Aim 2, Behavioral Biomarker Validation, we will validate inherited components of the behavioral biomarkers through the use of genome-wide analysis. We will use analysis of quantitative and dichotomous behavioral biomarker data using a quasi-Bayesian posterior probability method to elucidate the genetic architecture of risk, providing evidence of the nature of the inherited genetic component. For Aim 3, Genetic Biomarker Identification, we will identify specific DNA variations associated with genetic risk for autism and related disorders. We will test both common and rare variants, SNPs and CNVs, from candidate genes within the regions identified in Aim 2 and evaluate additional variants from the literature as potential factors modulating a network of risk-determining genes. Identification of susceptibility genes through the approaches proposed could provide important insights into biological basis of this illness, which could result in the development of novel treatments.

Connect on LinkedIn Connect on Google Scholar

Publications

                  Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Common genetic risk factors in ASD and ADHD co-occurring families. Hum Genet. 2022 Oct 17;  

                


                  Wong A, Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders. Genes (Basel). 2022 Jul 26; 13: 

                


                  Bossenbroek J, Ueyama Y, McCallinhart PE, Bartlett CW, Ray WC, Trask AJ. Improvement of automated analysis of coronary Doppler echocardiograms. Sci Rep. 2022 May 6; 12: 7490.

                


                  Johnson TS, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Zaid MA, Huang X, Wang Y, Bartlett C, Zhang Y, Walker BA, Liu Y, Huang K, Zhang J. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease. Genome Med. 2022 Feb 1; 14: 11.

                


                  Pavlek LR, Vudatala S, Bartlett CW, Buhimschi IA, Buhimschi CS, Rogers LK. MiR-29b is associated with perinatal inflammation in extremely preterm infants. Pediatr Res. 2021 Mar; 89: 889-893.

                


                  Backes CH, Söderström F, Ågren J, Sindelar R, Bartlett CW, Rivera BK, Mitchell CC, Frey HA, Shepherd EG, Nelin LD, Normann E. Outcomes following a comprehensive versus a selective approach for infants born at 22 weeks of gestation. J Perinatol. 2019 Jan; 39: 39-47.

                


                  Laasonen M, Smolander S, Lahti-Nuuttila P, Leminen M, Lajunen HR, Heinonen K, Pesonen AK, Bailey TM, Pothos EM, Kujala T, Leppänen PHT, Bartlett CW, Geneid A, Lauronen L, Service E, Kunnari S, Arkkila E. Understanding developmental language disorder - the Helsinki longitudinal SLI study (HelSLI): a study protocol. BMC Psychol. 2018 May 21; 6: 24.

                


                  Swaminathan R, Huang Y, Astbury C, Fitzgerald-Butt S, Miller K, Cole J, Bartlett C, Lin S. Clinical exome sequencing reports: current informatics practice and future opportunities. J Am Med Inform Assoc. 2017 Nov 1; 24: 1184-1191.

                


                  Sheppard KW, Boone KM, Gracious B, Klebanoff MA, Rogers LK, Rausch J, Bartlett C, Coury DL, Keim SA. Effect of Omega-3 and -6 Supplementation on Language in Preterm Toddlers Exhibiting Autism Spectrum Disorder Symptoms. J Autism Dev Disord. 2017 Nov; 47: 3358-3369.

                


                  Bruni M, Flax JF, Buyske S, Shindhelm AD, Witton C, Brzustowicz LM, Bartlett CW. Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds. Behav Genet. 2017 Mar; 47: 193-201.

View More Publications

Lab(s)

Battelle Center for Mathematical Medicine

Bartlett Lab

My laboratory seeks to identify genetic factors for language impairments. As animal models of language development are of limited utility, we examine DNA from families segregating specific language impairment or autism as part of two separate but interacting projects. These projects are heavily interdisciplinary, utilizing a wide range of molecular and computational methods developed in-house and though close collaborations with experts in statistics and computer science. We hope that use of genetics will allow for identification of at-risk children to promote early intervention.

Lab(s)

Battelle Center for Mathematical Medicine

Bartlett Lab

  • Battelle Center for Mathematical Medicine
  • Bartlett Lab

Neurogenetics:My long-term goal is to understand the molecular neurobiology of human language. However, moreso than any other cognitive neuroscience topic, the neurobiology of language is quite resistant to use of animal models except in extremely circumscribed ways. My approach is to use “forward genetics” whereby we map language and related traits into the human genome in language impaired patient and family studies using a mix of statistics and genomics. This work entails three levels of basic research and experimentation that feed into the larger project. 1) Statistical genetics research where we develop the statistical methods necessary to directly model and thereby answer our specific research questions. This work involves both analytical and computational methods. 2) Molecular genetic methods and assay development to generate the raw data used in our analyses. 3) Studies of gene expression in the human brain using methods that are similar to those for mapping cognitive traits, but these research questions involve finding directly functional genomic elements that are active in the human brain, such polymorphisms are good candidates biomarkers and mediators of cognitive performance.

Specific Language Impairment Research:Specific language impairment (SLI) is an idiopathic neurodevelopmental complex disorder consisting of clinically depressed language ability despite normal hearing, education and intelligence. Approximately 5-7 percentof school age children meet these criteria and represent the largest portion of children receiving special education services within the nation’s public school system costing on average an additional $2400/year per child while incurring less tax revenue due to lost educational opportunities. SLI is consistently heritable, defined either categorically or quantitatively (Bishop et al. 1995; Tomblin and Buckwalter 1998). To date, two genome-wide scans for SLI have been conducted (Bartlett et al. 2002; SLI_Consortium 2002). In a previous funding period we found compelling evidence for a susceptibility allele within our families selected for SLI on 13q21-22 (Bartlett et al. 2002) with a PPL of 53% (LOD=3.92). This finding was followed up with a replication PPL of 17 percent (LOD=2.62) (Bartlett et al. 2004); joint analysis of both datasets shows strong evidence for linkage to 13q21 with a PPL of 96.9 percent (LOD=7.86). We are executing a series of complementary approaches to assist in understanding the highly complex interrelationships between language and reading measures and how those relationships may underlie the SLI. To this end we are employing new multivariate approaches which are expected to 1) improve our understanding of how quantitative language and reading measures, some perhaps representing different etiologic mechanisms, relate to SLI as a diagnosis and 2) increase power to detect novel loci. Our strong linkage signal on 13q21 provides a solid foundation to perform a series of linkage/association analyses using uni- and multi-variate phenotypes including both categorical affection status and quantitative measures of language and related skills in order to dissect the multiple, heterogeneous, pathways to an SLI diagnosis.

Behavioral and Genetic Biomarker Development for Autism and Related Disorders:The overall goal of this project is to advance the development of behavioral and genetic biomarkers for autism and related disorders. While it is clear that autism has a strong inherited genetic component, very large scale genetic studies that have relied only on a general diagnosis of autism (spectrum) disorders (or other information only on affected individuals) have had limited success in identifying risk alleles, leaving a critical issue for the field. Behavioral biomarkers, especially language ability, have been used with some success to increase power in gene mapping, but to date studies have focused on detailed behavioral assessments only of subjects with autism and not their family members, despite an extensive literature defining increased rates of related phenotypes in family members. We will use our existing family set with an extensive existing database of clinical and genetic data from all family members, where each family contains at least one proband with autism and at least one proband with a language deficit, to define biomarkers for risk. For Aim 1, Behavioral Biomarker Development, we will develop a set of behavioral biomarkers of genetic risk for autism and related disorders. We will analyze our extensive behavioral testing database to determine which measures have the strongest genetic effects and further examine latent class structures for both data reduction and to reduce measurement error. We will conduct follow-up assessments on a subset of study participants to determine longitudinal stability of selected biomarkers. For Aim 2, Behavioral Biomarker Validation, we will validate inherited components of the behavioral biomarkers through the use of genome-wide analysis. We will use analysis of quantitative and dichotomous behavioral biomarker data using a quasi-Bayesian posterior probability method to elucidate the genetic architecture of risk, providing evidence of the nature of the inherited genetic component. For Aim 3, Genetic Biomarker Identification, we will identify specific DNA variations associated with genetic risk for autism and related disorders. We will test both common and rare variants, SNPs and CNVs, from candidate genes within the regions identified in Aim 2 and evaluate additional variants from the literature as potential factors modulating a network of risk-determining genes. Identification of susceptibility genes through the approaches proposed could provide important insights into biological basis of this illness, which could result in the development of novel treatments.

  • Connect on LinkedIn

  • Connect on Google Scholar

                   Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Common genetic risk factors in ASD and ADHD co-occurring families. Hum Genet. 2022 Oct 17;  



               Wong A, Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders. Genes (Basel). 2022 Jul 26; 13: 



               Bossenbroek J, Ueyama Y, McCallinhart PE, Bartlett CW, Ray WC, Trask AJ. Improvement of automated analysis of coronary Doppler echocardiograms. Sci Rep. 2022 May 6; 12: 7490.



               Johnson TS, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Zaid MA, Huang X, Wang Y, Bartlett C, Zhang Y, Walker BA, Liu Y, Huang K, Zhang J. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease. Genome Med. 2022 Feb 1; 14: 11.



               Pavlek LR, Vudatala S, Bartlett CW, Buhimschi IA, Buhimschi CS, Rogers LK. MiR-29b is associated with perinatal inflammation in extremely preterm infants. Pediatr Res. 2021 Mar; 89: 889-893.



               Backes CH, Söderström F, Ågren J, Sindelar R, Bartlett CW, Rivera BK, Mitchell CC, Frey HA, Shepherd EG, Nelin LD, Normann E. Outcomes following a comprehensive versus a selective approach for infants born at 22 weeks of gestation. J Perinatol. 2019 Jan; 39: 39-47.



               Laasonen M, Smolander S, Lahti-Nuuttila P, Leminen M, Lajunen HR, Heinonen K, Pesonen AK, Bailey TM, Pothos EM, Kujala T, Leppänen PHT, Bartlett CW, Geneid A, Lauronen L, Service E, Kunnari S, Arkkila E. Understanding developmental language disorder - the Helsinki longitudinal SLI study (HelSLI): a study protocol. BMC Psychol. 2018 May 21; 6: 24.



               Swaminathan R, Huang Y, Astbury C, Fitzgerald-Butt S, Miller K, Cole J, Bartlett C, Lin S. Clinical exome sequencing reports: current informatics practice and future opportunities. J Am Med Inform Assoc. 2017 Nov 1; 24: 1184-1191.



               Sheppard KW, Boone KM, Gracious B, Klebanoff MA, Rogers LK, Rausch J, Bartlett C, Coury DL, Keim SA. Effect of Omega-3 and -6 Supplementation on Language in Preterm Toddlers Exhibiting Autism Spectrum Disorder Symptoms. J Autism Dev Disord. 2017 Nov; 47: 3358-3369.



               Bruni M, Flax JF, Buyske S, Shindhelm AD, Witton C, Brzustowicz LM, Bartlett CW. Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds. Behav Genet. 2017 Mar; 47: 193-201.

View More Publications

  • Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Common genetic risk factors in ASD and ADHD co-occurring families. Hum Genet. 2022 Oct 17;
  • Wong A, Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders. Genes (Basel). 2022 Jul 26; 13:
  • Bossenbroek J, Ueyama Y, McCallinhart PE, Bartlett CW, Ray WC, Trask AJ. Improvement of automated analysis of coronary Doppler echocardiograms. Sci Rep. 2022 May 6; 12: 7490.
  • Johnson TS, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Zaid MA, Huang X, Wang Y, Bartlett C, Zhang Y, Walker BA, Liu Y, Huang K, Zhang J. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease. Genome Med. 2022 Feb 1; 14: 11.
  • Pavlek LR, Vudatala S, Bartlett CW, Buhimschi IA, Buhimschi CS, Rogers LK. MiR-29b is associated with perinatal inflammation in extremely preterm infants. Pediatr Res. 2021 Mar; 89: 889-893.
  • Backes CH, Söderström F, Ågren J, Sindelar R, Bartlett CW, Rivera BK, Mitchell CC, Frey HA, Shepherd EG, Nelin LD, Normann E. Outcomes following a comprehensive versus a selective approach for infants born at 22 weeks of gestation. J Perinatol. 2019 Jan; 39: 39-47.
  • Laasonen M, Smolander S, Lahti-Nuuttila P, Leminen M, Lajunen HR, Heinonen K, Pesonen AK, Bailey TM, Pothos EM, Kujala T, Leppänen PHT, Bartlett CW, Geneid A, Lauronen L, Service E, Kunnari S, Arkkila E. Understanding developmental language disorder - the Helsinki longitudinal SLI study (HelSLI): a study protocol. BMC Psychol. 2018 May 21; 6: 24.
  • Swaminathan R, Huang Y, Astbury C, Fitzgerald-Butt S, Miller K, Cole J, Bartlett C, Lin S. Clinical exome sequencing reports: current informatics practice and future opportunities. J Am Med Inform Assoc. 2017 Nov 1; 24: 1184-1191.
  • Sheppard KW, Boone KM, Gracious B, Klebanoff MA, Rogers LK, Rausch J, Bartlett C, Coury DL, Keim SA. Effect of Omega-3 and -6 Supplementation on Language in Preterm Toddlers Exhibiting Autism Spectrum Disorder Symptoms. J Autism Dev Disord. 2017 Nov; 47: 3358-3369.
  • Bruni M, Flax JF, Buyske S, Shindhelm AD, Witton C, Brzustowicz LM, Bartlett CW. Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds. Behav Genet. 2017 Mar; 47: 193-201.

Biography

        Christopher W. Bartlett, PhD, is a principal investigator in the Battelle Center for Mathematical Medicine at the Research Institute at Nationwide Children’s Hospital and an Associate Professor of Pediatrics at the Ohio State University. Dr. Bartlett's NIH funded research program primarily focuses on the genetics of language impairments in families including isolated impairments or in conjunction with autism spectrum disorder.

See Christopher W. Bartlett’s Curriculum Vitae (CV)

Biography

        Christopher W. Bartlett, PhD, is a principal investigator in the Battelle Center for Mathematical Medicine at the Research Institute at Nationwide Children’s Hospital and an Associate Professor of Pediatrics at the Ohio State University. Dr. Bartlett's NIH funded research program primarily focuses on the genetics of language impairments in families including isolated impairments or in conjunction with autism spectrum disorder.

See Christopher W. Bartlett’s Curriculum Vitae (CV)

Biography

        Christopher W. Bartlett, PhD, is a principal investigator in the Battelle Center for Mathematical Medicine at the Research Institute at Nationwide Children’s Hospital and an Associate Professor of Pediatrics at the Ohio State University. Dr. Bartlett's NIH funded research program primarily focuses on the genetics of language impairments in families including isolated impairments or in conjunction with autism spectrum disorder.

See Christopher W. Bartlett’s Curriculum Vitae (CV)

        Christopher W. Bartlett, PhD, is a principal investigator in the Battelle Center for Mathematical Medicine at the Research Institute at Nationwide Children’s Hospital and an Associate Professor of Pediatrics at the Ohio State University. Dr. Bartlett's NIH funded research program primarily focuses on the genetics of language impairments in families including isolated impairments or in conjunction with autism spectrum disorder.

See Christopher W. Bartlett’s Curriculum Vitae (CV)

See Christopher W. Bartlett’s Curriculum Vitae (CV)

Academic and Clinical Areas

Battelle Center for Mathematical Medicine

Faculty

Bartlett Lab

Principal Investigator

Primary Department

Battelle Center for Mathematical Medicine

Academic and Clinical Areas

Battelle Center for Mathematical Medicine

Faculty

Bartlett Lab

Principal Investigator

Primary Department

Battelle Center for Mathematical Medicine

Academic and Clinical Areas

Battelle Center for Mathematical Medicine

Faculty

Bartlett Lab

Principal Investigator

Primary Department

Battelle Center for Mathematical Medicine

Battelle Center for Mathematical Medicine

Faculty

Bartlett Lab

Principal Investigator

Primary Department

Battelle Center for Mathematical Medicine

  • Battelle Center for Mathematical Medicine
  • Faculty
  • Bartlett Lab
  • Principal Investigator
  • Primary Department
  • Battelle Center for Mathematical Medicine

Awards, Honors & Organizations

Bartlett et. al. in top ten best research papers on child development by Center of Excellence on Early Childhood Development, Université de Montréal, 2002 Graduate Fellowship for Academic Excellence, Johnson & Johnson, 1998 Inducted into Psy Chi, The National Honor Society for Psychology Students, 1998 - Present

Awards, Honors & Organizations

Bartlett et. al. in top ten best research papers on child development by Center of Excellence on Early Childhood Development, Université de Montréal, 2002 Graduate Fellowship for Academic Excellence, Johnson & Johnson, 1998 Inducted into Psy Chi, The National Honor Society for Psychology Students, 1998 - Present

Awards, Honors & Organizations

Bartlett et. al. in top ten best research papers on child development by Center of Excellence on Early Childhood Development, Université de Montréal, 2002 Graduate Fellowship for Academic Excellence, Johnson & Johnson, 1998 Inducted into Psy Chi, The National Honor Society for Psychology Students, 1998 - Present

Bartlett et. al. in top ten best research papers on child development by Center of Excellence on Early Childhood Development, Université de Montréal, 2002 Graduate Fellowship for Academic Excellence, Johnson & Johnson, 1998 Inducted into Psy Chi, The National Honor Society for Psychology Students, 1998 - Present

  • Bartlett et. al. in top ten best research papers on child development by Center of Excellence on Early Childhood Development, Université de Montréal, 2002
  • Graduate Fellowship for Academic Excellence, Johnson & Johnson, 1998
  • Inducted into Psy Chi, The National Honor Society for Psychology Students, 1998 - Present

Professional Experience

2014 - Present Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Associate Professor2014 - Present The Ohio State University College of Medicine, Associate Professor of Pediatrics2006 - 2014 The Ohio State University College of Medicine, Assistant Professor of Pediatrics2006 - 2014 Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Assistant Professor2006 - 2007 Center for Quantitative and Computational Biology, The Research Institute at Nationwide Children’s Hospital, Assistant Professor

Professional Experience

2014 - Present Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Associate Professor2014 - Present The Ohio State University College of Medicine, Associate Professor of Pediatrics2006 - 2014 The Ohio State University College of Medicine, Assistant Professor of Pediatrics2006 - 2014 Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Assistant Professor2006 - 2007 Center for Quantitative and Computational Biology, The Research Institute at Nationwide Children’s Hospital, Assistant Professor

Professional Experience

2014 - Present Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Associate Professor2014 - Present The Ohio State University College of Medicine, Associate Professor of Pediatrics2006 - 2014 The Ohio State University College of Medicine, Assistant Professor of Pediatrics2006 - 2014 Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Assistant Professor2006 - 2007 Center for Quantitative and Computational Biology, The Research Institute at Nationwide Children’s Hospital, Assistant Professor

2014 - Present Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Associate Professor2014 - Present The Ohio State University College of Medicine, Associate Professor of Pediatrics2006 - 2014 The Ohio State University College of Medicine, Assistant Professor of Pediatrics2006 - 2014 Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Assistant Professor2006 - 2007 Center for Quantitative and Computational Biology, The Research Institute at Nationwide Children’s Hospital, Assistant Professor

2014 - Present Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital, Associate Professor

Contact Information

Battelle Center for Mathematical Medicine

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W Bartlett

                    Abigail Wexner Research Institute575 Children's CrossroadColumbus, Ohio 43215 (map)

Contact Information

Battelle Center for Mathematical Medicine

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W Bartlett

                    Abigail Wexner Research Institute575 Children's CrossroadColumbus, Ohio 43215 (map)

Contact Information

Battelle Center for Mathematical Medicine

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W Bartlett

                    Abigail Wexner Research Institute575 Children's CrossroadColumbus, Ohio 43215 (map)

Battelle Center for Mathematical Medicine

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W Bartlett

                    Abigail Wexner Research Institute575 Children's CrossroadColumbus, Ohio 43215 (map)

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W Bartlett

                    Abigail Wexner Research Institute575 Children's CrossroadColumbus, Ohio 43215 (map)

Call us at: (614)355-5625

Fax us at: (614)355-2728

Email Christopher W Bartlett

                    Abigail Wexner Research Institute575 Children's CrossroadColumbus, Ohio 43215 (map)
  • Call us at:
  • (614)355-5625
  • Fax us at:
  • (614)355-2728
  • Email Christopher W Bartlett
  • Abigail Wexner Research Institute575 Children’s CrossroadColumbus, Ohio 43215 (map)