👤 Christina Lill

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4
Articles
3
Name variants
Also published as: Christina M Lill, Jennie R Lill
articles
Olena Ohlei, Yasmine Sommerer, Valerija Dobricic +20 more · 2023 · medRxiv : the preprint server for health sciences · Cold Spring Harbor Laboratory · added 2026-04-24
DNA methylation (DNAm) is an epigenetic mark with essential roles in disease development and predisposition. Here, we created genome-wide maps of methylation quantitative trait loci (meQTL) in three p Show more
DNA methylation (DNAm) is an epigenetic mark with essential roles in disease development and predisposition. Here, we created genome-wide maps of methylation quantitative trait loci (meQTL) in three peripheral tissues and used Mendelian randomization (MR) analyses to assess the potential causal relationships between DNAm and risk for two common neurodegenerative disorders, i.e. Alzheimer's disease (AD) and Parkinson's disease (PD). Genome-wide single nucleotide polymorphism (SNP; ~5.5M sites) and DNAm (~850K CpG sites) data were generated from whole blood (n=1,058), buccal (n=1,527) and saliva (n=837) specimens. We identified between 11 and 15 million genome-wide significant (p<10 Show less
📄 PDF DOI: 10.1101/2023.12.22.23300365
KANSL1
Christina Wittke, Sonja Petkovic, Valerija Dobricic +19 more · 2021 · Movement disorders : official journal of the Movement Disorder Society · Wiley · added 2026-04-24
This Movement Disorder Society Genetic mutation database Systematic Review focuses on monogenic atypical parkinsonism with mutations in the ATP13A2, DCTN1, DNAJC6, FBXO7, SYNJ1, and VPS13C genes. We s Show more
This Movement Disorder Society Genetic mutation database Systematic Review focuses on monogenic atypical parkinsonism with mutations in the ATP13A2, DCTN1, DNAJC6, FBXO7, SYNJ1, and VPS13C genes. We screened 673 citations and extracted genotypic and phenotypic data for 140 patients (73 families) from 77 publications. In an exploratory fashion, we applied an automated classification procedure via an ensemble of bootstrap-aggregated ("bagged") decision trees to distinguish these 6 forms of monogenic atypical parkinsonism and found a high accuracy of 86.5% (95%CI, 86.3%-86.7%) based on the following 10 clinical variables: age at onset, spasticity and pyramidal signs, hypoventilation, decreased body weight, minimyoclonus, vertical gaze palsy, autonomic symptoms, other nonmotor symptoms, levodopa response quantification, and cognitive decline. Comparing monogenic atypical with monogenic typical parkinsonism using 2063 data sets from Movement Disorder Society Genetic mutation database on patients with SNCA, LRRK2, VPS35, Parkin, PINK1, and DJ-1 mutations, the age at onset was earlier in monogenic atypical parkinsonism (24 vs 40 years; P = 1.2647 × 10 Show less
no PDF DOI: 10.1002/mds.28517
VPS13C
David Karasik, M Carola Zillikens, Yi-Hsiang Hsu +154 more · 2019 · The American journal of clinical nutrition · Oxford University Press · added 2026-04-24
David Karasik, M Carola Zillikens, Yi-Hsiang Hsu, Ali Aghdassi, Kristina Akesson, Najaf Amin, Inês Barroso, David A Bennett, Lars Bertram, Murielle Bochud, Ingrid B Borecki, Linda Broer, Aron S Buchman, Liisa Byberg, Harry Campbell, Natalia Campos-Obando, Jane A Cauley, Peggy M Cawthon, John C Chambers, Zhao Chen, Nam H Cho, Hyung Jin Choi, Wen-Chi Chou, Steven R Cummings, Lisette C P G M de Groot, Phillip L De Jager, Ilja Demuth, Luda Diatchenko, Michael J Econs, Gudny Eiriksdottir, Anke W Enneman, Joel Eriksson, Johan G Eriksson, Karol Estrada, Daniel S Evans, Mary F Feitosa, Mao Fu, Christian Gieger, Harald Grallert, Vilmundur Gudnason, Launer J Lenore, Caroline Hayward, Albert Hofman, Georg Homuth, Kim M Huffman, Lise B Husted, Thomas Illig, Erik Ingelsson, Till Ittermann, John-Olov Jansson, Toby Johnson, Reiner Biffar, Joanne M Jordan, Antti Jula, Magnus Karlsson, Kay-Tee Khaw, Tuomas O Kilpeläinen, Norman Klopp, Jacqueline S L Kloth, Daniel L Koller, Jaspal S Kooner, William E Kraus, Stephen Kritchevsky, Zoltán Kutalik, Teemu Kuulasmaa, Johanna Kuusisto, Markku Laakso, Jari Lahti, Thomas Lang, Bente L Langdahl, Markus M Lerch, Joshua R Lewis, Christina Lill, Lars Lind, Cecilia Lindgren, Yongmei Liu, Gregory Livshits, Östen Ljunggren, Ruth J F Loos, Mattias Lorentzon, Jian'an Luan, Robert N Luben, Ida Malkin, Fiona E McGuigan, Carolina Medina-Gomez, Thomas Meitinger, Håkan Melhus, Dan Mellström, Karl Michaëlsson, Braxton D Mitchell, Andrew P Morris, Leif Mosekilde, Maria Nethander, Anne B Newman, Jeffery R O'Connell, Ben A Oostra, Eric S Orwoll, Aarno Palotie, Munro Peacock, Markus Perola, Annette Peters, Richard L Prince, Bruce M Psaty, Katri Räikkönen, Stuart H Ralston, Samuli Ripatti, Fernando Rivadeneira, John A Robbins, Jerome I Rotter, Igor Rudan, Veikko Salomaa, Suzanne Satterfield, Sabine Schipf, Chan Soo Shin, Albert V Smith, Shad B Smith, Nicole Soranzo, Timothy D Spector, Alena Stancáková, Kari Stefansson, Elisabeth Steinhagen-Thiessen, Lisette Stolk, Elizabeth A Streeten, Unnur Styrkarsdottir, Karin M A Swart, Patricia Thompson, Cynthia A Thomson, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Emmi Tikkanen, Gregory J Tranah, André G Uitterlinden, Cornelia M Van Duijn, Natasja M van Schoor, Liesbeth Vandenput, Peter Vollenweider, Henry Völzke, Jean Wactawski-Wende, Mark Walker, Nicholas J Wareham, Dawn Waterworth, Michael N Weedon, H-Erich Wichmann, Elisabeth Widen, Frances M K Williams, James F Wilson, Nicole C Wright, Laura M Yerges-Armstrong, Lei Yu, Weihua Zhang, Jing Hua Zhao, Yanhua Zhou, Carrie M Nielson, Tamara B Harris, Serkalem Demissie, Douglas P Kiel, Claes Ohlsson Show less
Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce Show more
Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce the power to identify genetic signals having an association with both lean mass and fat mass. To determine the impact of different fat mass adjustments on genetic architecture of LM and identify additional LM loci. We performed genome-wide association analyses for whole-body LM (20 cohorts of European ancestry with n = 38,292) measured using dual-energy X-ray absorptiometry) or bioelectrical impedance analysis, adjusted for sex, age, age2, and height with or without fat mass adjustments (Model 1 no fat adjustment; Model 2 adjustment for fat mass as a percentage of body mass; Model 3 adjustment for fat mass in kilograms). Seven single-nucleotide polymorphisms (SNPs) in separate loci, including one novel LM locus (TNRC6B), were successfully replicated in an additional 47,227 individuals from 29 cohorts. Based on the strengths of the associations in Model 1 vs Model 3, we divided the LM loci into those with an effect on both lean mass and fat mass in the same direction and refer to those as "sumo wrestler" loci (FTO and MC4R). In contrast, loci with an impact specifically on LM were termed "body builder" loci (VCAN and ADAMTSL3). Using existing available genome-wide association study databases, LM increasing alleles of SNPs in sumo wrestler loci were associated with an adverse metabolic profile, whereas LM increasing alleles of SNPs in "body builder" loci were associated with metabolic protection. In conclusion, we identified one novel LM locus (TNRC6B). Our results suggest that a genetically determined increase in lean mass might exert either harmful or protective effects on metabolic traits, depending on its relation to fat mass. Show less
no PDF DOI: 10.1093/ajcn/nqy272
MC4R
Marinella G Callow, Hoanh Tran, Lilian Phu +12 more · 2011 · PloS one · PLOS · added 2026-04-24
Canonical Wnt signaling is controlled intracellularly by the level of β-catenin protein, which is dependent on Axin scaffolding of a complex that phosphorylates β-catenin to target it for ubiquitylati Show more
Canonical Wnt signaling is controlled intracellularly by the level of β-catenin protein, which is dependent on Axin scaffolding of a complex that phosphorylates β-catenin to target it for ubiquitylation and proteasomal degradation. This function of Axin is counteracted through relocalization of Axin protein to the Wnt receptor complex to allow for ligand-activated Wnt signaling. AXIN1 and AXIN2 protein levels are regulated by tankyrase-mediated poly(ADP-ribosyl)ation (PARsylation), which destabilizes Axin and promotes signaling. Mechanistically, how tankyrase limits Axin protein accumulation, and how tankyrase levels and activity are regulated for this function, are currently under investigation. By RNAi screening, we identified the RNF146 RING-type ubiquitin E3 ligase as a positive regulator of Wnt signaling that operates with tankyrase to maintain low steady-state levels of Axin proteins. RNF146 also destabilizes tankyrases TNKS1 and TNKS2 proteins and, in a reciprocal relationship, tankyrase activity reduces RNF146 protein levels. We show that RNF146, tankyrase, and Axin form a protein complex, and that RNF146 mediates ubiquitylation of all three proteins to target them for proteasomal degradation. RNF146 is a cytoplasmic protein that also prevents tankyrase protein aggregation at a centrosomal location. Tankyrase auto-PARsylation and PARsylation of Axin is known to lead to proteasome-mediated degradation of these proteins, and we demonstrate that, through ubiquitylation, RNF146 mediates this process to regulate Wnt signaling. Show less
📄 PDF DOI: 10.1371/journal.pone.0022595
AXIN1