A Phenome-Wide Association Study (PheWAS) of Late Onset Alzheimer Disease Genetic Risk in Children of European Ancestry at Middle Childhood: Results from the ABCD Study.
| Title: | A Phenome-Wide Association Study (PheWAS) of Late Onset Alzheimer Disease Genetic Risk in Children of European Ancestry at Middle Childhood: Results from the ABCD Study. |
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| Authors: | Gorelik AJ; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Paul SE; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Karcher NR; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.; Johnson EC; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.; Nagella I; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Blaydon L; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Modi H; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Hansen IS; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.; Colbert SMC; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.; Baranger DAA; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Norton SA; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Spears I; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Gordon B; Department of Radiology, Washington University in Saint Louis, 660 South Euclid Ave, Box 8225, St. Louis, MO, 63110, USA.; Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St Louis, MO, USA.; Zhang W; Department of Radiology, Washington University in Saint Louis, 660 South Euclid Ave, Box 8225, St. Louis, MO, 63110, USA.; Hill PL; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Oltmanns TF; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Bijsterbosch JD; Department of Radiology, Washington University in Saint Louis, 660 South Euclid Ave, Box 8225, St. Louis, MO, 63110, USA.; Agrawal A; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.; Hatoum AS; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA.; Bogdan R; Department of Psychological and Brain Sciences, Washington University in Saint Louis, One Booking Drive, St. Louis, MO, 63130, USA. rbogdan@wustl.edu. |
| Source: | Behavior genetics [Behav Genet] 2023 May; Vol. 53 (3), pp. 249-264. Date of Electronic Publication: 2023 Apr 18. |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S. |
| Language: | English |
| Journal Info: | Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 0251711 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-3297 (Electronic) Linking ISSN: 00018244 NLM ISO Abbreviation: Behav Genet Subsets: MEDLINE |
| Imprint Name(s): | Publication: 1999- : New York : Kluwer Academic/Plenum Publishers; Original Publication: Westport, Conn., Greenwood Periodicals. |
| MeSH Terms: | Alzheimer Disease*/genetics ; Alzheimer Disease*/psychology; Apolipoproteins E/genetics ; Child ; Humans ; Cognition ; Genotype ; Risk Factors |
| Abstract: | Genetic risk for Late Onset Alzheimer Disease (AD) has been associated with lower cognition and smaller hippocampal volume in healthy young adults. However, whether these and other associations are present during childhood remains unclear. Using data from 5556 genomically-confirmed European ancestry youth who completed the baseline session of the ongoing the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®), our phenome-wide association study estimating associations between four indices of genetic risk for late-onset AD (i.e., AD polygenic risk scores (PRS), APOE rs429358 genotype, AD PRS with the APOE region removed (ADPRS-APOE), and an interaction between ADPRS-APOE and APOE genotype) and 1687 psychosocial, behavioral, and neural phenotypes revealed no significant associations after correction for multiple testing (all ps > 0.0002; all pfdr > 0.07). These data suggest that AD genetic risk may not phenotypically manifest during middle-childhood or that effects are smaller than this sample is powered to detect.; (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.) |
| References: | Albert MS, DeKosky ST, Dickson D et al (2011) The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7:270–279. https://doi.org/10.1016/j.jalz.2011.03.008. (PMID: 10.1016/j.jalz.2011.03.008215142493312027); Alexander S, Kerr ME, Kim Y et al (2007) Apolipoprotein E4 allele presence and functional outcome after severe traumatic brain injury. J Neurotrauma 24:790–797. https://doi.org/10.1089/neu.2006.0133. (PMID: 10.1089/neu.2006.013317518534); Austin PC (2010) Estimating multilevel logistic regression models when the number of clusters is low: a comparison of different statistical software procedures. Int J Biostat 6:16. https://doi.org/10.2202/1557-4679.1195. (PMID: 10.2202/1557-4679.1195209491282949382); Bartoń K (2009) MuMIn: multi-model inference.; Basser PJ, Mattiello J, Lebihan D (1994) Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson Ser B 103:247–254. https://doi.org/10.1006/jmrb.1994.1037. (PMID: 10.1006/jmrb.1994.1037); Bates D, Mächler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67:1–48. https://doi.org/10.18637/jss.v067.i01. (PMID: 10.18637/jss.v067.i01); Baurley JW, Edlund CK, Pardamean CI et al (2016) Smokescreen: a targeted genotyping array for addiction research. BMC Genomics 17:145. https://doi.org/10.1186/s12864-016-2495-7. (PMID: 10.1186/s12864-016-2495-7269212594769529); Bekris LM, Yu C-E, Bird TD, Tsuang DW (2010) Genetics of Alzheimer disease. J Geriatr Psychiatry Neurol 23:213–227. https://doi.org/10.1177/0891988710383571. (PMID: 10.1177/0891988710383571210451633044597); Bellenguez C, Küçükali F, Jansen IE et al (2022) New insights into the genetic etiology of Alzheimer’s disease and related dementias. Nat Genet 54:412–436. https://doi.org/10.1038/s41588-022-01024-z. (PMID: 10.1038/s41588-022-01024-z353799929005347); Cruchaga C, Kauwe JSK, Nowotny P et al (2012) Cerebrospinal fluid APOE levels: an endophenotype for genetic studies for Alzheimer’s disease. Hum Mol Genet 21:4558–4571. https://doi.org/10.1093/hmg/dds296. (PMID: 10.1093/hmg/dds296228213963459471); Dale AM, Fischl B, Sereno MI (1999) Cortical surface-based analysis I. Segmentation and surface reconstruction. Neuroimage 9:179–194. https://doi.org/10.1006/nimg.1998.0395. (PMID: 10.1006/nimg.1998.03959931268); Dean DC, Jerskey BA, Chen K et al (2014) Brain differences in infants at differential genetic risk for late-onset Alzheimer disease: a cross-sectional imaging study. JAMA Neurol 71:11–22. https://doi.org/10.1001/jamaneurol.2013.4544. (PMID: 10.1001/jamaneurol.2013.4544242760924056558); Desikan RS, Ségonne F, Fischl B et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31:968–980. https://doi.org/10.1016/j.neuroimage.2006.01.021. (PMID: 10.1016/j.neuroimage.2006.01.02116530430); Dondu A, Sevincoka L, Akyol A, Tataroglu C (2015) Is obsessive-compulsive symptomatology a risk factor for Alzheimer-type dementia? Psychiatry Res 225:381–386. https://doi.org/10.1016/j.psychres.2014.12.010. (PMID: 10.1016/j.psychres.2014.12.01025576369); Elliott ML, Knodt AR, Ireland D et al (2020) What is the test-retest reliability of common task-functional MRI measures? New empirical evidence and a meta-analysis. Psychol Sci 31:792–806. https://doi.org/10.1177/0956797620916786. (PMID: 10.1177/0956797620916786324891417370246); Escott-Price V, Hardy J (2022) Genome-wide association studies for Alzheimer’s disease: bigger is not always better. Brain Commun 4:fcac125. https://doi.org/10.1093/braincomms/fcac125. (PMID: 10.1093/braincomms/fcac125356633829155614); Evans SL, Dowell NG, Prowse F et al (2020) Mid age APOE ε4 carriers show memory-related functional differences and disrupted structure-function relationships in hippocampal regions. Sci Rep 10:3110. https://doi.org/10.1038/s41598-020-59272-0. (PMID: 10.1038/s41598-020-59272-0320802117033211); Filippini N, MacIntosh BJ, Hough MG et al (2009) Distinct patterns of brain activity in young carriers of the APOE-epsilon4 allele. Proc Natl Acad Sci USA 106:7209–7214. https://doi.org/10.1073/pnas.0811879106. (PMID: 10.1073/pnas.0811879106193573042678478); Fleisher A, Grundman M, Jack CR Jr et al (2005) Sex, apolipoprotein E ε4 status, and hippocampal volume in mild cognitive impairment. Arch Neurol 62:953–957. https://doi.org/10.1001/archneur.62.6.953. (PMID: 10.1001/archneur.62.6.95315956166); GBD 2019 Dementia Forecasting Collaborators (2022) Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019. Lancet Public Health 7:e105–e125. https://doi.org/10.1016/S2468-2667(21)00249-8.; Ge T, Chen C-Y, Ni Y et al (2019) Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nat Commun 10:1776. https://doi.org/10.1038/s41467-019-09718-5. (PMID: 10.1038/s41467-019-09718-5309924496467998); Gellersen HM, Guell X, Sami S (2021) Differential vulnerability of the cerebellum in healthy ageing and Alzheimer’s disease. NeuroImage 30:102605. https://doi.org/10.1016/j.nicl.2021.102605. (PMID: 10.1016/j.nicl.2021.102605337357877974323); Ghassabian A, Sundaram R, Bell E et al (2016) Gross motor milestones and subsequent development. Pediatrics 138:e20154372. https://doi.org/10.1542/peds.2015-4372. (PMID: 10.1542/peds.2015-4372273544574925077); Gordon EM, Laumann TO, Adeyemo B et al (2016) Generation and evaluation of a cortical area parcellation from resting-state correlations. Cereb Cortex 26:288–303. https://doi.org/10.1093/cercor/bhu239. (PMID: 10.1093/cercor/bhu23925316338); Grabher BJ (2018) Effects of Alzheimer disease on patients and their family. J Nucl Med Technol 46:335–340. https://doi.org/10.2967/jnmt.118.218057. (PMID: 10.2967/jnmt.118.21805730139888); Graham A, Livingston G, Purnell L, Huntley J (2022) Mild traumatic brain injuries and future risk of developing Alzheimer’s disease: systematic review and meta-analysis. J Alzheimers Dis 87:969–979. https://doi.org/10.3233/JAD-220069. (PMID: 10.3233/JAD-22006935491789); Green P, MacLeod CJ (2016) SIMR: an R package for power analysis of generalized linear mixed models by simulation. Methods Ecol Evol 7:493–498. https://doi.org/10.1111/2041-210X.12504. (PMID: 10.1111/2041-210X.12504); Hendriks S, Peetoom K, Bakker C et al (2021) Global prevalence of young-onset dementia: a systematic review and meta-analysis. JAMA Neurol 78:1080–1090. https://doi.org/10.1001/jamaneurol.2021.2161. (PMID: 10.1001/jamaneurol.2021.216134279544); Hong EP, Park JW (2012) Sample size and statistical power calculation in genetic association studies. Genomics Inf 10:117–122. https://doi.org/10.5808/GI.2012.10.2.117. (PMID: 10.5808/GI.2012.10.2.1173480678); Jacobs HIL, Hopkins DA, Mayrhofer HC et al (2018) The cerebellum in Alzheimer’s disease: evaluating its role in cognitive decline. Brain J Neurol 141:37–47. https://doi.org/10.1093/brain/awx194. (PMID: 10.1093/brain/awx194); Johnson EC, Demontis D, Thorgeirsson TE et al (2020) A large-scale genome-wide association study meta-analysis of cannabis use disorder. Lancet Psychiatry 7:1032–1045. https://doi.org/10.1016/S2215-0366(20)30339-4. (PMID: 10.1016/S2215-0366(20)30339-4330960467674631); Joo YY, Moon S-Y, Wang H-H et al (2022) Association of genome-wide polygenic scores for multiple psychiatric and common traits in preadolescent youths at risk of suicide. JAMA Network Open 5:e2148585. https://doi.org/10.1001/jamanetworkopen.2021.48585. (PMID: 10.1001/jamanetworkopen.2021.48585351885568861848); Korologou-Linden R, Bhatta L, Brumpton BM et al (2022) The causes and consequences of Alzheimer’s disease: phenome-wide evidence from Mendelian randomization. Nat Commun 13:4726. https://doi.org/10.1038/s41467-022-32183-6. (PMID: 10.1038/s41467-022-32183-6359534829372151); Karcher NR, Paul SE, Johnson EC et al (2022) Psychotic-like experiences and polygenic liability in the adolescent brain cognitive development study. Biol Psychiatry Cognit Neurosci Neuroimaging 7:45–55. https://doi.org/10.1016/j.bpsc.2021.06.012. (PMID: 10.1016/j.bpsc.2021.06.012); Kunkle BW, Grenier-Boley B, Sims R et al (2019) Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat Genet 51:414–430. https://doi.org/10.1038/s41588-019-0358-2. (PMID: 10.1038/s41588-019-0358-2308200476463297); Kunkle BW, Schmidt M, Klein H-U et al (2021) Novel Alzheimer disease risk loci and pathways in African American individuals using the African genome resources panel: a meta-analysis. JAMA Neurol 78:102–113. https://doi.org/10.1001/jamaneurol.2020.3536. (PMID: 10.1001/jamaneurol.2020.353633074286); Ladouceur CD, Kerestes R, Schlund MW et al (2019) Neural systems underlying reward cue processing in early adolescence: the role of puberty and pubertal hormones. Psychoneuroendocrinology 102:281–291. https://doi.org/10.1016/j.psyneuen.2018.12.016. (PMID: 10.1016/j.psyneuen.2018.12.01630639923); Lam M, Awasthi S, Watson HJ et al (2020) RICOPILI: rapid imputation for COnsortias PIpeLIne. Bioinformatics 36:930–933. https://doi.org/10.1093/bioinformatics/btz633. (PMID: 10.1093/bioinformatics/btz63331393554); Liu JZ, Erlich Y, Pickrell JK (2017) Case-control association mapping by proxy using family history of disease. Nat Genet 49:325–331. https://doi.org/10.1038/ng.3766. (PMID: 10.1038/ng.376628092683); Livingston G, Huntley J, Sommerlad A et al (2020) Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet 396:413–446. https://doi.org/10.1016/S0140-6736(20)30367-6. (PMID: 10.1016/S0140-6736(20)30367-6327389377392084); Martin AR, Kanai M, Kamatani Y et al (2019) Clinical use of current polygenic risk scores may exacerbate health disparities. Nat Genet 51:584–591. https://doi.org/10.1038/s41588-019-0379-x. (PMID: 10.1038/s41588-019-0379-x309269666563838); Mol MO, van der Lee SJ, Hulsman M et al (2022) Mapping the genetic landscape of early-onset Alzheimer’s disease in a cohort of 36 families. Alzheimers Res Ther 14:77. https://doi.org/10.1186/s13195-022-01018-3. (PMID: 10.1186/s13195-022-01018-3356505859158156); Muir AM, Ching C, Santhalingam V et al (2021) The relationship between APOE genotype and subcortical volume: a UK Biobank study (N=36,920). Alzheimer’s Dementia 17:e055650. https://doi.org/10.1002/alz.055650. (PMID: 10.1002/alz.055650); Murray GK, Jones PB, Kuh D, Richards M (2007) Infant developmental milestones and subsequent cognitive function. Ann Neurol 62:128–136. https://doi.org/10.1002/ana.21120. (PMID: 10.1002/ana.21120174878773465788); Murray AN, Chandler HL, Lancaster TM (2021) Multimodal hippocampal and amygdala subfield volumetry in polygenic risk for Alzheimer’s disease. Neurobiol Aging 98:33–41. https://doi.org/10.1016/j.neurobiolaging.2020.08.022. (PMID: 10.1016/j.neurobiolaging.2020.08.022332275677886309); Nagelkerke NJD Miscellanea A note on a general definition of the coefficient of determination.; Nichols E, Szoeke CEI, Vollset SE et al (2019) Global, regional, and national burden of Alzheimer’s disease and other dementias, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol 18:88–106. https://doi.org/10.1016/S1474-4422(18)30403-4. (PMID: 10.1016/S1474-4422(18)30403-4); Nie X, Sun Y, Wan S et al (2017) Subregional structural alterations in hippocampus and nucleus accumbens correlate with the clinical impairment in patients with Alzheimer’s disease clinical spectrum: parallel combining volume and vertex-based approach. Front Neurol 8:399. https://doi.org/10.3389/fneur.2017.00399. (PMID: 10.3389/fneur.2017.00399288610335559429); O’Dwyer L, Lamberton F, Matura S et al (2012) Reduced hippocampal volume in healthy young ApoE4 carriers: an MRI study. PLoS ONE 7:e48895. https://doi.org/10.1371/journal.pone.0048895. (PMID: 10.1371/journal.pone.0048895231528153494711); Ohi K, Ochi R, Noda Y et al (2021) Polygenic risk scores for major psychiatric and neurodevelopmental disorders contribute to sleep disturbance in childhood: Adolescent Brain Cognitive Development (ABCD) Study. Transl Psychiatry 11:1–11. https://doi.org/10.1038/s41398-021-01308-8. (PMID: 10.1038/s41398-021-01308-8); Paul SE, Hatoum AS, Fine JD et al (2021) Associations between prenatal cannabis exposure and childhood outcomes: results from the ABCD study. JAMA Psychiatry 78:64–76. https://doi.org/10.1001/jamapsychiatry.2020.2902. (PMID: 10.1001/jamapsychiatry.2020.290232965490); Reitz C, Rogaeva E, Beecham GW (2020) Late-onset vs nonmendelian early-onset Alzheimer disease: a distinction without a difference? Neurol Genet 6:e512. https://doi.org/10.1212/NXG.0000000000000512. (PMID: 10.1212/NXG.0000000000000512332250657673282); Sakai J (2020) Core Concept: How synaptic pruning shapes neural wiring during development and possibly, in disease. Proc Natl Acad Sci USA 117:16096–16099. https://doi.org/10.1073/pnas.2010281117. (PMID: 10.1073/pnas.2010281117325811257368197); Sims R, Hill M, Williams J (2020) The multiplex model of the genetics of Alzheimer’s disease. Nat Neurosci 23:311–322. https://doi.org/10.1038/s41593-020-0599-5. (PMID: 10.1038/s41593-020-0599-532112059); Stafford J, Chung WT, Sommerlad A et al (2022) Psychiatric disorders and risk of subsequent dementia: systematic review and meta-analysis of longitudinal studies. Int J Geriatr Psychiatry 37:5711. https://doi.org/10.1002/gps.5711. (PMID: 10.1002/gps.5711); Taliun D, Harris DN, Kessler MD et al (2021) Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature 590:290–299. https://doi.org/10.1038/s41586-021-03205-y. (PMID: 10.1038/s41586-021-03205-y335688197875770); Tiemeier H, Lenroot RK, Greenstein DK et al (2010) Cerebellum development during childhood and adolescence: a longitudinal morphometric MRI study. Neuroimage 49:63–70. https://doi.org/10.1016/j.neuroimage.2009.08.016. (PMID: 10.1016/j.neuroimage.2009.08.01619683586); Volkow ND, Koob GF, Croyle RT et al (2018) The conception of the ABCD study: from substance use to a broad NIH collaboration. Dev Cogn Neurosci 32:4–7. https://doi.org/10.1016/j.dcn.2017.10.002. (PMID: 10.1016/j.dcn.2017.10.00229051027); Walhovd KB, Fjell AM, Sørensen Ø et al (2020) Genetic risk for Alzheimer disease predicts hippocampal volume through the human lifespan. Neurol Genet 6:e506. https://doi.org/10.1212/NXG.0000000000000506. (PMID: 10.1212/NXG.0000000000000506331345087577559); Wang H, Abbas KM, Abbasifard M et al (2020) Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019. The Lancet 396:1160–1203. https://doi.org/10.1016/S0140-6736(20)30977-6. (PMID: 10.1016/S0140-6736(20)30977-6); Wightman DP, Jansen IE, Savage JE et al (2021) A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease. Nat Genet 53:1276–1282. https://doi.org/10.1038/s41588-021-00921-z. (PMID: 10.1038/s41588-021-00921-z34493870); Zhang Z, Wang M, Liu X (2022) C-reactive protein and risk of Alzheimer’s disease. Neurobiol Aging 109:259–263. https://doi.org/10.1016/j.neurobiolaging.2021.08.010. (PMID: 10.1016/j.neurobiolaging.2021.08.01034538509) |
| Grant Information: | U24 DA041147 United States DA NIDA NIH HHS; U01 DA041120 United States DA NIDA NIH HHS; K23 MH121792 United States MH NIMH NIH HHS; R01 DA054750 United States DA NIDA NIH HHS; U01 DA041093 United States DA NIDA NIH HHS; U24 DA041123 United States DA NIDA NIH HHS; F31 AA029934 United States AA NIAAA NIH HHS; U01 DA041156 United States DA NIDA NIH HHS; K01 DA051759 United States DA NIDA NIH HHS; K01 AA030083 United States AA NIAAA NIH HHS; U01 DA041025 United States DA NIDA NIH HHS; U01 DA041089 United States DA NIDA NIH HHS; U01 DA041106 United States DA NIDA NIH HHS; U01 DA041117 United States DA NIDA NIH HHS; U01 DA041148 United States DA NIDA NIH HHS; U01 DA041174 United States DA NIDA NIH HHS; U01 DA041134 United States DA NIDA NIH HHS; U01 DA041022 United States DA NIDA NIH HHS; U01 DA041028 United States DA NIDA NIH HHS; U01 DA041048 United States DA NIDA NIH HHS |
| Contributed Indexing: | Keywords: APOE; Alzheimer disease; Imaging; Middle childhood; Phenome-wide association study; Polygenic risk scores |
| Substance Nomenclature: | 0 (Apolipoproteins E) |
| Entry Date(s): | Date Created: 20230418 Date Completed: 20230504 Latest Revision: 20240923 |
| Update Code: | 20260130 |
| PubMed Central ID: | PMC10309061 |
| DOI: | 10.1007/s10519-023-10140-3 |
| PMID: | 37071275 |
| Database: | MEDLINE |
Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.