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Table 2 Summary of candidate genes used in AD pathology

From: A review of brain imaging biomarker genomics in Alzheimer’s disease: implementation and perspectives

Year

Author

Dataset

Methods

Novel genes

1991

[7]

Goate et al.

Gene Cloning

Molecular studies

APP gene

1993

[10]

Corder et al.

Gene Cloning

Molecular studies

APOE gene

1995

[8, 9]

Sherrington et al.

Gene Cloning

Molecular studies

2 genes

(PSEN1 and PSEN2)

2009–2011

[16, 2730]

Lambert et al.

GERAD

EADI

CHARGE

ADGC

Meta-analysis

11 genes

(CLU, PICALM, CR1, BIN1, CD2AP, CD33, EPHA1, MS4A4A, ABCA7, MS4A6A, and MS4A4E)

2013

[31]

Lambert et al.

IGAP

(n = 74,046)

Meta-analysis

11 genes

(HLA-DRB5, SORL1, PTK2B, SLC24A4-RIN3, ZCWPW1, NME8, FERMT2, CELF1, INPP5D, MEF2C, and CASS4)

2017

[32]

Sims et al.

IGAP

(n = 85,133)

Meta-analysis

3 genes

(PLCG2, ABI3, and TREM2)

2017

[33]

Liu et al.

UK Biobank

(n = 116,196)

Meta-analysis

4 genes

(HBEGF, ECHDC3, SPPL2A, and SCIMP)

2018

[34]

Marioni et al.

UK Biobank

(n = 314,278)

Meta-analysis

3 genes

(ADAM10, KAT8, and ACE)

2019

[21]

Jansen et al.

PGC-ALZ

IGAP

ADSP

(n = 455,266)

Meta-analysis

8 genes

(ADAMTS4, HESX1, CLNK, CNTAP2, APH1B, ABI3, ALPK2, and ACO74212.3)

2019

[20]

Kunkle et al.

IGAP

(n = 94,437)

Meta-analysis

5 genes

(IQCK, ACE, ADAM10, ADAMTS1, and WWOX)

2020

[24]

Schwartzentruber et al.

UK Biobank

(n = 408,942)

Meta-analysis

4 genes

(CCDC6, TSPAN14, NCK2, and SPRED2)

2021

[25]

Wightman et al.

1,126,563 individuals

Meta-analysis

7 genes

(AGRN, TNIP1, TMEM106B, GRN, HAVCR2, NTN5, and LILRB2)