Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder

Major depressive disorder (MDD) is a common but serious psychiatric disorder with significant levels of morbidity and mortality. Recent genome-wide association studies (GWAS) on common variants increase our understanding of MDD; however, the underlying genetic basis remains largely unknown. Many studies have been proposed to explore the genetics of complex diseases from a viewpoint of the “missing heritability” by considering low-frequency and rare variants, copy-number variations, and other types of genetic variants. Here we developed a novel computational and statistical strategy to investigate the “missing heritability” of MDD. We applied Hamming distance on common, low-frequency, and rare single-nucleotide polymorphism (SNP) sets to measure genetic distance between two individuals, and then built the multi-dimensional scaling (MDS) pictures. Whole-exome genotyping data from a Los Angeles Mexican-American cohort (203 MDD and 196 controls) and a European-ancestry cohort (473 MDD and 497 controls) were examined using our proposed methodology. MDS plots showed very significant separations between MDD cases and healthy controls for low-frequency SNP set (P value < 2.2e−16) and rare SNP set (P value = 7.681e−12). Our results suggested that low-frequency and rare variants may play more significant roles in the genetics of MDD.

[1]  M. Wong,et al.  Clinical outcomes and genome-wide association for a brain methylation site in an antidepressant pharmacogenetics study in Mexican Americans. , 2014, The American journal of psychiatry.

[2]  P. Visscher,et al.  Estimating missing heritability for disease from genome-wide association studies. , 2011, American journal of human genetics.

[3]  Patrick F. Sullivan,et al.  Genetic architectures of psychiatric disorders: the emerging picture and its implications , 2012, Nature Reviews Genetics.

[4]  J. Ott,et al.  HDR: a statistical two-step approach successfully identifies disease genes in autosomal recessive families , 2016, Journal of Human Genetics.

[5]  M. Wong,et al.  Whole-genome single nucleotide variant distribution on genomic regions and its relationship to major depression , 2017, Psychiatry Research.

[6]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[7]  P. Fox,et al.  Genome-wide linkage on chromosome 10q26 for a dimensional scale of major depression. , 2016, Journal of affective disorders.

[8]  B. Baune,et al.  Clinical, Functional, and Biological Correlates of Cognitive Dimensions in Major Depressive Disorder – Rationale, Design, and Characteristics of the Cognitive Function and Mood Study (CoFaM-Study) , 2016, Front. Psychiatry.

[9]  G. Lettre,et al.  Rare variant association studies: considerations, challenges and opportunities , 2015, Genome Medicine.

[10]  Jason H. Moore,et al.  Missing heritability and strategies for finding the underlying causes of complex disease , 2010, Nature Reviews Genetics.

[11]  J. Long,et al.  Illumina human exome genotyping array clustering and quality control , 2014, Nature Protocols.

[12]  Richard W. Hamming,et al.  Error detecting and error correcting codes , 1950 .

[13]  J. Alvidrez,et al.  Cultural Influences on Causal Beliefs About Depression Among Latino Immigrants , 2013, Journal of transcultural nursing : official journal of the Transcultural Nursing Society.

[14]  M. Nei,et al.  Molecular Evolution and Phylogenetics , 2000 .

[15]  J. Flint,et al.  The Genetic Architecture of Major Depressive Disorder in Han Chinese Women , 2017, JAMA psychiatry.

[16]  D. Hinds,et al.  Identification of 15 genetic loci associated with risk of major depression in individuals of European descent , 2016, Nature Genetics.

[17]  E. Lander,et al.  The mystery of missing heritability: Genetic interactions create phantom heritability , 2012, Proceedings of the National Academy of Sciences.

[18]  J. Licinio,et al.  Sequence variations of ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1, CRHR1 and NTRK2: association with major depression and antidepressant response in Mexican-Americans , 2009, Molecular Psychiatry.

[19]  O. Franco,et al.  Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms , 2017, Molecular Psychiatry.

[20]  Julio Licinio,et al.  From monoamines to genomic targets: a paradigm shift for drug discovery in depression , 2004, Nature Reviews Drug Discovery.

[21]  M. Wong,et al.  Single-nucleotide variant proportion in genes: a new concept to explore major depression based on DNA sequencing data , 2017, Journal of Human Genetics.

[22]  P. Sullivan,et al.  Genetic epidemiology of major depression: review and meta-analysis. , 2000, The American journal of psychiatry.

[23]  M. Wong,et al.  Research and treatment approaches to depression , 2001, Nature Reviews Neuroscience.

[24]  G. Abecasis,et al.  Rare-variant association analysis: study designs and statistical tests. , 2014, American journal of human genetics.

[25]  Jurg Ott,et al.  Genetic linkage analysis in the age of whole-genome sequencing , 2015, Nature Reviews Genetics.

[26]  Warren W. Kretzschmar,et al.  Sparse whole genome sequencing identifies two loci for major depressive disorder , 2015, Nature.

[27]  M. Wong,et al.  The PHF21B gene is associated with major depression and modulates the stress response , 2016, Molecular Psychiatry.

[28]  F. Lohoff Overview of the Genetics of Major Depressive Disorder , 2010, Current psychiatry reports.

[29]  K. Lesch,et al.  CRSN Symposium : Focus on Depression , Part I Symposium du CRSN : le point sur la dépression , première partie Gene – environment interaction and the genetics of depression , 2004 .

[30]  J. Flint,et al.  The Genetics of Major Depression , 2014, Neuron.

[31]  M. Wong,et al.  A novel strategy for clustering major depression individuals using whole-genome sequencing variant data , 2017, Scientific Reports.

[32]  Robert M. Maier,et al.  Genetic Basis of Complex Genetic Disease: The Contribution of Disease Heterogeneity to Missing Heritability , 2014, Current Epidemiology Reports.

[33]  W. Torgerson Multidimensional scaling: I. Theory and method , 1952 .

[34]  Judy H. Cho,et al.  Finding the missing heritability of complex diseases , 2009, Nature.

[35]  J. Licinio,et al.  Elevated cortisol levels and increased rates of diabetes and mood symptoms in Soviet Union-born Jewish immigrants to Germany , 2005, Molecular Psychiatry.

[36]  R. Kessler,et al.  Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. , 1994, Archives of general psychiatry.

[37]  Ruth C. Brown,et al.  Genetic Determinants of Depression: Recent Findings and Future Directions , 2015, Harvard review of psychiatry.

[38]  Olga V. Demler,et al.  Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. , 2005, Archives of general psychiatry.

[39]  Alan D. Lopez THE GLOBAL BURDEN OF DISEASE 1990-2020 , 2001 .

[40]  J. Ott,et al.  Beyond Homozygosity Mapping: Family-Control analysis based on Hamming distance for prioritizing variants in exome sequencing , 2015, Scientific Reports.

[41]  M. Wong,et al.  Prediction of susceptibility to major depression by a model of interactions of multiple functional genetic variants and environmental factors , 2012, Molecular Psychiatry.