Juan Manuel Peralta

Mr. Juan Manuel Peralta

orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
24 August 2020 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
Xihao LiXihao Li
Xihao Li
Zilin LiZilin Li
Zilin Li
HZHufeng Zhou
Hufeng Zhou
SGSheila M. Gaynor
Sheila M. Gaynor
YLYaowu Liu
Yaowu Liu
XLXihong Lin
Xihong Lin

1 February 2010 in Archives of General Psychiatry
Verified
Journal Article
Open access
PDF file
DGDavid C. Glahn
David C. Glahn
LALaura Almasy
Laura Almasy
MBMarcela Barguil
Marcela Barguil
EHElizabeth Hare
Elizabeth Hare
JPJuan Manuel Peralta
Juan Manuel Peralta
MEMichael A. Escamilla
Michael A. Escamilla
Despite considerable evidence that the risk for bipolar disorder is inherited, the molecular genetic basis for this illness remains elusive. A recent genome-wide association analysis with more than 5000 cases and 6000 control subjects implicated 2 risk genes for the illness: ANK3 and CACNA1C.1 Because these genes regulate voltage-gated sodium and calcium channels, respectively, the findings suggest that ion channel dysfunction may play an important role in the pathophysiologic process of bipolar disorder. However, as noted by the authors, these genes have relatively small risk ratios, explaining little of the genetic contribution to the illness. Given the high heritability and familial relative risk of bipolar disorder, there is little doubt that additional genes are involved in the etiology of the illness. The identification of these genes is of paramount importance because they hold the potential for spurring novel treatments for this common and debilitating illness.

29 November 2011 in BMC Proceedings
Verified
Journal Article
Open access
PDF file
LALaura Almasy
Laura Almasy
TDThomas D Dyer
Thomas D Dyer
JPJuan Manuel Peralta
Juan Manuel Peralta
JKJack W Kent
Jack W Kent
JCJac C Charlesworth
Jac C Charlesworth
JBJohn Blangero
John Blangero
The data set simulated for Genetic Analysis Workshop 17 was designed to mimic a subset of data that might be produced in a full exome screen for a complex disorder and related risk factors in order to permit workshop participants to investigate issues of study design and statistical genetic analysis. Real sequence data from the 1000 Genomes Project formed the basis for simulating a common disease trait with a prevalence of 30% and three related quantitative risk factors in a sample of 697 unrelated individuals and a second sample of 697 individuals in large, extended pedigrees. Called genotypes for 24,487 autosomal markers assigned to 3,205 genes and simulated affection status, quantitative traits, age, sex, pedigree relationships, and cigarette smoking were provided to workshop participants. The simulating model included both common and rare variants with minor allele frequencies ranging from 0.07% to 25.8% and a wide range of effect sizes for these variants. Genotype-smoking interaction effects were included for variants in one gene. Functional variants were concentrated in genes selected from specific biological pathways and were selected on the basis of the predicted deleteriousness of the coding change. For each sample, unrelated individuals and family, 200 replicates of the phenotypes were simulated.

5 December 2016 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
ACAudrey Y Chu
Audrey Y Chu
XDXuan Deng
Xuan Deng
VFVirginia A Fisher
Virginia A Fisher
ADAlexander Drong
Alexander Drong
YZYang Zhang
Yang Zhang
CFCaroline S Fox
Caroline S Fox

10 October 2006 in American Journal of Medical Genetics Part B: Neuropsychiatric Genetics
Verified
Journal Article
Closed access
PDF file
DGDavid C. Glahn
David C. Glahn
LALaura Almasy
Laura Almasy
JBJohn Blangero
John Blangero
GBGary M. Burk
Gary M. Burk
JEJose Estrada
Jose Estrada
MEMichael A. Escamilla
Michael A. Escamilla

30 June 2016 in Nature Communications
Verified
Journal Article
Open access
PDF file
ANAlexandra M. Nicholson
Alexandra M. Nicholson
NFNiCole A. Finch
NiCole A. Finch
MAMarcio Augusto Afonso de Almeida
Marcio Augusto Afonso de Almeida
RPRalph B. Perkerson
Ralph B. Perkerson
MBMarka van Blitterswijk
Marka van Blitterswijk
RRRosa Rademakers
Rosa Rademakers
Progranulin (GRN) loss-of-function mutations leading to progranulin protein (PGRN) haploinsufficiency are prevalent genetic causes of frontotemporal dementia. Reports also indicated PGRN-mediated neuroprotection in models of Alzheimer’s and Parkinson’s disease; thus, increasing PGRN levels is a promising therapeutic for multiple disorders. To uncover novel PGRN regulators, we linked whole-genome sequence data from 920 individuals with plasma PGRN levels and identified the prosaposin (PSAP) locus as a new locus significantly associated with plasma PGRN levels. Here we show that both PSAP reduction and overexpression lead to significantly elevated extracellular PGRN levels. Intriguingly, PSAP knockdown increases PGRN monomers, whereas PSAP overexpression increases PGRN oligomers, partly through a protein–protein interaction. PSAP-induced changes in PGRN levels and oligomerization replicate in human-derived fibroblasts obtained from a GRN mutation carrier, further supporting PSAP as a potential PGRN-related therapeutic target. Future studies should focus on addressing the relevance and cellular mechanism by which PGRN oligomeric species provide neuroprotection.