Cross-Disorder Group of the Psychiatric Genomics Consortium. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet. 2013;45:984–94.

Article  PubMed Central  Google Scholar 

Mullins N, Forstner AJ, O’Connell KS, Coombes B, Coleman JRI, Qiao Z, et al. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat Genet. 2021;53:817–29.

Article  CAS  PubMed  PubMed Central  Google Scholar 

McIntyre RS, Berk M, Brietzke E, Goldstein BI, López-Jaramillo C, Kessing LV, et al. Bipolar disorders. Lancet. 2020;396:1841–56.

Article  CAS  PubMed  Google Scholar 

Forty L, Ulanova A, Jones L, Jones I, Gordon-Smith K, Fraser C, et al. Comorbid medical illness in bipolar disorder. Br J Psychiatry. 2014;205:465–72.

Article  PubMed  PubMed Central  Google Scholar 

McElroy SL, Altshuler LL, Suppes T, Keck PE, Frye MA, Denicoff KD, et al. Axis I psychiatric comorbidity and its relationship to historical illness variables in 288 patients with bipolar disorder. AJP. 2001;158:420–6.

Article  CAS  Google Scholar 

Soreca I, Fagiolini A, Frank E, Houck PR, Thompson WK, Kupfer DJ. Relationship of general medical burden, duration of illness and age in patients with bipolar I disorder. J Psychiatr Res. 2008;42:956–61.

Article  PubMed  Google Scholar 

He H, Hu C, Ren Z, Bai L, Gao F, Lyu J. Trends in the incidence and DALYs of bipolar disorder at global, regional, and national levels: Results from the global burden of Disease Study 2017. J Psychiatr Res. 2020;125:96–105.

Article  PubMed  Google Scholar 

Kilbourne AM, Perron BE, Mezuk B, Welsh D, Ilgen M, Bauer MS. Co-occurring conditions and health-related quality of life in patients with bipolar disorder. Psychosom Med. 2009;71:894–900.

Article  CAS  PubMed  Google Scholar 

Fullerton JM, Nurnberger JI. Polygenic risk scores in psychiatry: Will they be useful for clinicians? F1000Research. 2019;8:1293.

Article  CAS  Google Scholar 

Lopes FL, Zhu K, Purves KL, Song C, Ahn K, Hou L, et al. Polygenic risk for anxiety influences anxiety comorbidity and suicidal behavior in bipolar disorder. Transl Psychiatry. 2020;10:298.

Article  PubMed  PubMed Central  Google Scholar 

Sanchez Ruiz JA, Coombes BJ, Pendegraft RS, Ozerdem A, McElroy SL, Cuellar-Barboza AB, et al. Pharmacotherapy exposure as a marker of disease complexity in bipolar disorder: associations with clinical & genetic risk factors. Psychiatry Res. 2023;323:115174.

Article  CAS  PubMed  Google Scholar 

Coombes BJ, Millischer V, Batzler A, Larrabee B, Hou L, Papiol S, et al. Association of attention-deficit/hyperactivity disorder and depression polygenic scores with lithium response: a Consortium for Lithium Genetics Study. Complex Psychiatry. 2021;7:80–89.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Coombes BJ, Markota M, Mann JJ, Colby C, Stahl E, Talati A, et al. Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores. Transl Psychiatry. 2020;10:314.

Article  PubMed  PubMed Central  Google Scholar 

Schubert KO, Thalamuthu A, Amare AT, Frank J, Streit F, Adl M, et al. Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients. Transl Psychiatry. 2021;11:606.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Denny JC, Ritchie MD, Basford MA, Pulley JM, Bastarache L, Brown-Gentry K, et al. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics. 2010;26:1205–10.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Linder JE, Bastarache L, Hughey JJ, Peterson JF. The role of electronic health records in advancing genomic medicine. Annu Rev Genom Hum Genet. 2021;22:219–38.

Article  Google Scholar 

Smoller JW. The use of electronic health records for psychiatric phenotyping and genomics. Am J Med Genet Part B: Neuropsychiatr Genet. 2018;177:601–12.

Article  Google Scholar 

Bastarache L. Using phecodes for research with the electronic health record: from PheWAS to PheRS. Annu Rev Biomed Data Sci. 2021;4:1–19.

Article  PubMed  PubMed Central  Google Scholar 

Kember RL, Merikangas AK, Verma SS, Verma A, Judy R, Damrauer SM, et al. Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data from european ancestry individuals. Biol Psychiatry. 2021;89:236–45.

Article  CAS  PubMed  Google Scholar 

Fang Y, Fritsche LG, Mukherjee B, Sen S, Richmond-Rakerd LS. Polygenic liability to depression is associated with multiple medical conditions in the electronic health record: phenome-wide association study of 46,782 individuals. Biol Psychiatry. 2022;92:923–31.

Article  PubMed  PubMed Central  Google Scholar 

Olson JE, Ryu E, Hathcock MA, Gupta R, Bublitz JT, Takahashi PY, et al. Characteristics and utilisation of the Mayo Clinic Biobank, a clinic-based prospective collection in the USA: cohort profile. BMJ Open. 2019;9:e032707.

Article  PubMed  PubMed Central  Google Scholar 

Frye MA, McElroy SL, Fuentes M, Sutor B, Schak KM, Galardy CW, et al. Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses. Int J Bipolar Disord. 2015;3:14.

Article  PubMed  PubMed Central  Google Scholar 

Denny JC, Bastarache L, Ritchie MD, Carroll RJ, Zink R, Mosley JD, et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat Biotechnol. 2013;31:1102–11.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wei W-Q, Bastarache LA, Carroll RJ, Marlo JE, Osterman TJ, Gamazon ER, et al. Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record. PLoS ONE. 2017;12:e0175508.

Article  PubMed  PubMed Central  Google Scholar 

Wu P, Gifford A, Meng X, Li X, Campbell H, Varley T, et al. Mapping ICD-10 and ICD-10-CM codes to Phecodes: workflow development and initial evaluation. JMIR Med Inf. 2019;7:e14325.

Article  Google Scholar 

Das S, Forer L, Schönherr S, Sidore C, Locke AE, Kwong A, et al. Next-generation genotype imputation service and methods. Nat Genet. 2016;48:1284–7.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Fuchsberger C, Abecasis GR, Hinds DA. minimac2: faster genotype imputation. Bioinformatics. 2015;31:782–4.

Article  CAS  PubMed  Google Scholar 

Privé F, Arbel J, Vilhjálmsson BJ. LDpred2: better, faster, stronger. Bioinformatics. 2021;36:5424–31.

Article  PubMed  Google Scholar 

Denny JC, Bastarache L, Roden DM. Phenome-wide association studies as a tool to advance precision medicine. Annu Rev Genom Hum Genet. 2016;17:353–73.

Article  CAS  Google Scholar 

P. Vatcheva K, Lee M. Multicollinearity in regression analyses conducted in epidemiologic studies. Epidemiology. 2016;06:227 https://doi.org/10.4172/2161-1165.1000227

Article  Google Scholar 

Low YS, Gallego B, Shah NH. Comparing high-dimensional confounder control methods for rapid cohort studies from electronic health records. J Comp Eff Res. 2016;5:179–92.

Article  PubMed  Google Scholar 

Ahuja Y, Kim N, Liang L, Cai T, Dahal K, Seyok T, et al. Leveraging electronic health records data to predict multiple sclerosis disease activity. Ann Clin Transl Neurol. 2021;8:800–10.

Article  PubMed  PubMed Central  Google Scholar 

Dyas AR, Zhuang Y, Meguid RA, Henderson WG, Madsen HJ, Bronsert MR, et al. Development and validation of a model for surveillance of postoperative bleeding complications using structured electronic health records data. Surgery. 2022;172:1728–32.

Article  PubMed  Google Scholar 

Wu Y, Fan J, Peissig P, Berg R, Tafti AP, Yin J, et al. Quantifying predictive capability of electronic health records for the most harmful breast cancer. Proc SPIE Int Soc Opt Eng. 2018;10577:105770J.

PubMed  PubMed Central  Google Scholar 

Fritsche LG, Gruber SB, Wu Z, Schmidt EM, Zawistowski M, Moser SE, et al. Association of polygenic risk scores for multiple cancers in a phenome-wide study: results from the michigan genomics initiative. Am J Hum Genet. 2018;102:1048–61.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Andreassen OA, Hindley GFL, Frei O, Smeland OB. New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications. World Psychiatry. 2023;22:4–24.

Article  PubMed  PubMed Central  Google Scholar 

Carroll RJ, Bastarache L, Denny JC. R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment. Bioinformatics. 2014;30:2375–6.

Article  CAS  PubMed  PubMed Central