Browsing by Author "Scheltens P."

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    Basic Science and Pathogenesis
    (2025-12-01) Senanarong V.; Senanarong V.; Rattanabannakit C.; Dujada P.; Raksthaput A.; Chaichanettee S.; Wongkom N.; Raksthaput A.; Chaichanettee S.; Limwongse C.; Scheltens P.; Scheltens P.; Rosa-Neto P.; Rosa-Neto P.; Gauthier S.; Gauthier S.; Senanarong V.; Mahidol University
    BACKGROUND: Early-onset dementia (EOD) is a uncommon form of dementia that afflicts people before age 65. Only a few studies analyzing the genetics of EOD have been performed in Thai population. EOD remains a challenge due to the diverse genetic and clinical heterogeneity of these diseases. The aim of this study was to investigate the genetic spectrum of Thai EOD and those with familial history of dementia. METHOD: 150 subjects with EOD AND 18 individuals with familial dementia were recruited. Targeted next generation (NGS) analyses were performed to screen 38 genes associated with dementia. RESULT: Subject characteristics were demonstrated in table 1. Fifteen had pathogenic variants. Among pathogenic (47%) and likely pathogenic (53%) variants, 5 (33.33%) were in PSEN1 (c.417G>T, p.Met139Ile), (c.344A>G, p.Tyr115Cys), (c.817G>A, p.Glu273Lys), (c.817G>A, p.Glu273Lys), (c.485T>C, p.Ile162Thr)); 2 (13.33%) in CSF1R (c.704T>G, p.Val235Gly), (c.2522A>G, p.Tyr841Cys); 1(6.67%) each in ABCA7 (c.5571-1G>C, p.?), SNCB (c.372G>A, p.Gln124=), SORL1 (c.2212G>A, p.Gly738Arg), APP (c.2149G>A, p.Val717Ile), VAPB (c.301G>T, p.Asp101Tyr), GRN (c.276C>A, p.Cys92Ter), SOD1 (c.143T>C, p.Val48Ala), and NOTCH3 (c.1630C>T, p.Arg544Cys). Among these, the PSEN1 variant c.817G>A (p.Glu273Lys) had not previously been reported. 61 had variants of uncertain significance (VUS). Graphs 1-3 showed results of NGS for dementia in the whole cohort, in those with pathogenic variants, and in those with VUS. CONCLUSION: Our study demonstrated the genetic spectrum of EOD and familial dementia in Thai patients. The utilization of next-generation sequencing could help deciphering the genetic causes of Alzheimer's disease. The genetic testing of known causal genes in EOD patients can help make a precise diagnosis. We acknowledged Thailand Science Research and Innovation for supporting this study.
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    Biomarkers
    (2025-12-01) Senanarong V.; Thientunyakit T.; Rattanabannakit C.; Wongkom N.; Dujada P.; Raksthaput A.; Chaichanettee S.; Phoyoo P.; Wachirutmangur L.; Scheltens P.; Senanarong V.; Mahidol University
    BACKGROUND: Our objective of this study is to identify suitable local cut-off values of plasma-based biomarkers in Alzheimer disease (AD) in the discrimination of AD and non-AD subgroups in Thai population. METHOD: We conducted a prospective study in 51 individuals with clinically diagnosed AD (15 had amyloid PET positive (≥ 30 centiloid, CL), 16 had CSF Aβ42 ≤547 pg/mL and CSF pTau 181 >57 pg/mL regarded as amyloid positive AD), 34 individuals with clinically diagnosed non-AD dementia (9 had amyloid PET negative, 25 had CSF Aβ42 and CSF pTau181 negative), and 12 individuals with mild cognitive impairment (MCI) or normal controls (6 had amyloid PET negative and 6 had CSF Aβ42 and CSF pTau181 negative). Aβ-PET using 18F-florbetapir and plasma biomarkers (Aβ40, Aβ42, p-tau181, pTau 217, Glial fibrillary acidic protein (GFAP)) were obtained in all subjects within 6 months before or after the PET study. The quantitative analysis of Aβ-PET to obtain Centiloid (CL) followed the standard method using the SPM8 pipeline. Blood biomarker analysis utilized Simoa® Quanterix immunoassay. CSF Aβ42, t-Tau and p-Tau were measured separately, in duplicate, by commercially available sandwich ELISA kits (Innotest; Innogenetics/Fujirebio, Ghent, Belgium). Participants underwent a standardized diagnostic dementia evaluation. RESULT: Among 97 individuals, 54 (55.7%) amyloid positive and 43(44.3%) amyloid negative individuals were included in this blood biomarkers validation study. Mean age was 65.86(8.01) years, mean TMSE was 19.57(7.44) and mean MOCA was 15.48(7.27). Mean(SD) plasma Aβ 42/40, pTau181, pTau 217, NFL, and GFAP were 0.054(0.013) pg/mL, 37.591(18.975) pg/mL, 1.088(0.949) pg/mL, 102.703(412.308) pg/mL, and 162.459(107.223) pg/mL respectively. Utilizing single cut off from ROC analysis: the cut off points are as followed; for plasma Aβ42/40≤0.054pg/mL (AUC(SE)=0.716(0.064), p <0.0001, accuracy 72.63(62.52-81.28)); plasma pTau181>32.7pg/mL (AUC(SE)=0.812(0.058), p <0.0001, accuracy73.20(63.24-81.68)); plasma pTau217>0.522pg/mL (AUC(SE)=0.856(0.056), p <0.0001, accuracy87.14(76.99-93.95)); GFAP>119pg/mL (AUC(SE)=0.796(0.058), p <0.0001, accuracy77.89(68.22-85.77)). For high and low cut- points, the results were shown in table 1. CONCLUSION: Plasma biomarkers showed promising diagnostic performances and potential clinical usefulness in diagnosing dementia. Plasma p-tau217 was best differentiates AD positive from AD negative groups, followed by plasma GFAP, pTau181, and Aβ42/40 ratio. Thank you Health Systems Research Institute (Thailand) grant support for this study.
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    Cost-utility analysis of cerebrospinal fluid versus blood biomarkers for early detection of Alzheimer's disease and mild cognitive impairment in Thailand: a modeling study
    (2026-04-02) Leelahavarong P.; Prawjaeng J.; Angkab P.; Wongkom N.; Scheltens P.; Srinonprasert V.; Senanarong V.; Leelahavarong P.; Mahidol University