Table Info

Table 1.

Examination of the relationship between different circulating progenitor or mature endothelial cells and the risk of AD/dementia by using Cox proportional hazards regression models after adjusting for covariates

Circulating cells	Number/mL (%) Median [Q1, Q3]	AD HR (95% CI)	P value	All-cause dementia HR (95% CI)	P value
CD34+CD133+	2.61 × 10⁴ [1.65 × 10⁴, 4.39 × 10⁴] 0.031 [0.020, 0.049]	0.64 (0.44, 0.94) n = 1,340	0.02^*	0.63 (0.45, 0.87) n = 1,362	0.006^*
CD34+CD133–	2.13 × 10⁴ [1.38 × 10⁴, 3.19 × 10⁴] 0.025 [0.017, 0.038]	0.79 (0.49, 1.27) n = 1,340	0.33	0.74 (0.50, 1.10) n = 1,362	0.14
CD34–CD133+	3.06 × 10⁴ [2.33 × 10⁴, 4.15 × 10⁴] 0.037 [0.028, 0.047]	0.56 (0.28, 1.14) n = 1,340	0.11	0.81 (0.46, 1.43) n = 1,362	0.47
CD34–CD133–	8.59 × 10⁷ [6.91 × 10⁷, 10.56 × 10⁷] 99.90 [99.90, 99.90]	342.92 (0.62, 1.91 × 10⁵) n = 1,340	0.07	62.05 (0.37, 1.03 × 10⁴) n = 1,362	0.11
CD34+	6.36 × 10⁴ [4.44 × 10⁴, 9.51 × 10⁴] 0.076 [0.053, 0.110]	0.62 (0.36, 1.04) n = 1,415	0.07	0.61 (0.39, 0.96) n = 1,436	0.03^*
CD34+/KDR+	3.38 × 10⁶ [1.96 × 10⁶, 5.71 × 10⁶] 3.96 [2.33, 6.58]	0.91 (0.65, 1.28) n = 1,416	0.59	0.91 (0.68, 1.23) n = 1,437	0.55
CD31+/CD45–	5.14 × 10⁵ [2.93 × 10⁵, 8.78 × 10⁵] 0.60 [0.36, 1.01]	0.85 (0.62, 1.17) n = 1,431	0.32	0.85 (0.65, 1.11) n = 1,453	0.24
CD31+	1.73 × 10⁷ [1.19 × 10⁷, 2.42 × 10⁷] 20.24 [15.12, 26.00]	0.86 (0.43, 1.70) n = 1,400	0.65	0.74 (0.42, 1.31) n = 1,421	0.30
CD31–	3.11 × 10⁷ [2.35 × 10⁷, 4.02 × 10⁷] 39.39 [29.98, 47.93]	1.46 (0.69, 3.08) n = 1,400	0.32	1.64 (0.85, 3.16) n = 1,421	0.14
CD31+DIM	3.36 × 10⁷ [2.38 × 10⁷, 4.43 × 10⁷] 39.03 [31.99, 46.82]	0.73 (0.32, 1.66) n = 1,400	0.45	0.73 (0.36, 1.48) n = 1,421	0.38
CD31+lymphoid	6.57 × 10⁷ [5.38 × 10⁷, 8.22 × 10⁷] 79.76 [74.00, 84.88]	1.91 (0.16, 22.65) n = 1,400	0.61	2.76 (0.32, 24.12) n = 1,421	0.36

The concentration (cell number/mL) and the proportion (%) of different circulating endothelial cell (EPCs) and EMCs are illustrated in the 2nd column. Cox proportional hazards regression models were used to study the relationship between the proportions (%) of different subtypes of EPCs and EMCs (log-transformed) and the risk of AD or all-cause dementia after adjusting for age, sex, years of education, APOE ε4, and vascular diseases. HR with 95% CI with P values is shown. ^* P value significant < 0.05; CI: confidence interval; HR: hazard ratio; Q: quartile

Supplementary materials

The supplementary materials for this article are available at: https://www.explorationpub.com/uploads/Article/file/1001216_sup_1.pdf

Declarations

Acknowledgments

We want to express our thanks to the FHS participants for their decades of dedication and to the FHS staff for their hard work in collecting and preparing the data.

Author contributions

YW and J Huang: Data curation, Investigation, Formal analysis, Writing—original draft. TFAA: Data curation, Investigation, Formal analysis, Writing—review & editing. YZ and QT: Data curation, Investigation. JM, MA, GVD, AB, AG, MR, BG, J Han, KLL, and TDS: Formal analysis, Writing—review & editing. RA and LAF: Supervision, Formal analysis, Writing—review & editing. XZ and WQQ: Conceptualization, Writing—review & editing, Methodology, Supervision.

Conflicts of interest

Lindsay A. Farrer who is the Editor-in-Chief of Exploration of Medicine had no involvement in the decision-making or the review process of this manuscript.

Ethical approval

The FHS was approved by the Institutional Review Board of Boston University, and all participants provided written informed consent. The ROS and MAP studies were approved by the Institutional Review Board of Rush University Medical Center. All participants signed an informed consent, an Anatomic Gift Act for brain donation, and a repository consent to allow their data and biospecimens to be shared.

Consent to participate

Informed consent to participate in the study was obtained from all participants.

Consent to publication

Not applicable.

Availability of data and materials

The FHS data is available at dbGaP (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000007.v33.p14) upon reasonable request/application. The ROSMAP data is available at the AD Knowledge Portal (https://adknowledgeportal.org). The other datasets that support the findings of this study are available from the corresponding author upon reasonable request.

Funding

This study was supported by National Institute on Aging grants [U19-AG068753, RF1-AG057519, and R01-AG048927]. The FHS data collection was supported by the National Heart, Lung, and Blood Institute contract [N01-HC-25195]. The sponsor institutes did not play any role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Copyright

References

Custodia A, Ouro A, Romaus-Sanjurjo D, Pías-Peleteiro JM, de Vries HE, Castillo J, et al. Endothelial progenitor cells and vascular alterations in Alzheimer’s disease. Front Aging Neurosci. 2022;13:811210. [DOI] [PubMed] [PMC]

Zhang Z, Gan Q, Han J, Tao Q, Qiu WQ, Madri JA. CD31 as a probable responding and gate-keeping protein of the blood-brain barrier and the risk of Alzheimer’s disease. J Cereb Blood Flow Metab. 2023;43:1027–41. [DOI] [PubMed]

Vagnucci AH Jr, Li WW. Alzheimer’s disease and angiogenesis. Lancet. 2003;361:605–8. [DOI]

Chou RC, Kane M, Ghimire S, Gautam S, Gui J. Treatment for rheumatoid arthritis and risk of Alzheimer’s disease: a nested case-control analysis. CNS Drugs. 2016;30:1111–20. [DOI] [PubMed] [PMC]

Drake JD, Chambers AB, Ott BR, Daiello LA; Alzheimer’s Disease Neuroimaging Initiative. Peripheral markers of vascular endothelial dysfunction show independent but additive relationships with brain-based biomarkers in association with functional impairment in Alzheimer’s disease. J Alzheimers Dis. 2021;80:1553–65. [DOI] [PubMed] [PMC]

Zhang Z, Na H, Gan Q, Tao Q, Alekseyev Y, Hu J, et al. Monomeric C-reactive protein via endothelial CD31 for neurovascular inflammation in an ApoE genotype-dependent pattern: a risk factor for Alzheimer’s disease? Aging Cell. 2021;20:e13501. [DOI] [PubMed] [PMC]

Cao W, Zheng H. Peripheral immune system in aging and Alzheimer’s disease. Mol Neurodegener. 2018;13:51. [DOI] [PubMed] [PMC]

Liebner S, Dijkhuizen RM, Reiss Y, Plate KH, Agalliu D, Constantin G. Functional morphology of the blood-brain barrier in health and disease. Acta Neuropathol. 2018;135:311–36. [DOI] [PubMed] [PMC]

Rigato M, Avogaro A, Fadini GP. Levels of circulating progenitor cells, cardiovascular outcomes and death: a meta-analysis of prospective observational studies. Circ Res. 2016;118:1930–9. [DOI] [PubMed]

10.

Yamaguchi T, Kanayasu-Toyoda T, Uchida E. Angiogenic cell therapy for severe ischemic diseases. Biol Pharm Bull. 2013;36:176–81. [DOI] [PubMed]

11.

Maslovaric M, Fatic N, Delević E. State of the art of stem cell therapy for ischaemic cardiomyopathy. Part 1. Angiol Sosud Khir. 2019;25:39–52. [DOI] [PubMed]

12.

Miller-Kasprzak E, Jagodziński PP. Endothelial progenitor cells as a new agent contributing to vascular repair. Arch Immunol Ther Exp (Warsz). 2007;55:247–59. [DOI] [PubMed]

13.

Kong XD, Zhang Y, Liu L, Sun N, Zhang MY, Zhang JN. Endothelial progenitor cells with Alzheimer’s disease. Chin Med J (Engl). 2011;124:901–6. [PubMed]

14.

Maler JM, Spitzer P, Lewczuk P, Kornhuber J, Herrmann M, Wiltfang J. Decreased circulating CD34⁺ stem cells in early Alzheimer’s disease: evidence for a deficient hematopoietic brain support? Mol Psychiatry. 2006;11:1113–5. [DOI] [PubMed]

15.

Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families. The Framingham offspring study. Am J Epidemiol. 1979;110:281–90. [DOI] [PubMed]

16.

Cheng S, Cohen KS, Shaw SY, Larson MG, Hwang SJ, McCabe EL, et al. Association of colony-forming units with coronary artery and abdominal aortic calcification. Circulation. 2010;122:1176–82. [DOI] [PubMed] [PMC]

17.

Cheng S, Wang N, Larson MG, Palmisano JN, Mitchell GF, Benjamin EJ, et al. Circulating angiogenic cell populations, vascular function, and arterial stiffness. Atherosclerosis. 2012;220:145–50. [DOI] [PubMed] [PMC]

18.

Cohen KS, Cheng S, Larson MG, Cupples LA, McCabe EL, Wang YA, et al. Circulating CD34⁺ progenitor cell frequency is associated with clinical and genetic factors. Blood. 2013;121:e50–6. [DOI] [PubMed] [PMC]

19.

Muggeridge D, Dodd J, Ross MD. CD34⁺ progenitors are predictive of mortality and are associated with physical activity in cardiovascular disease patients. Atherosclerosis. 2021;333:108–15. [DOI] [PubMed]

20.

Satizabal CL, Beiser AS, Chouraki V, Chêne G, Dufouil C, Seshadri S. Incidence of dementia over three decades in the framingham heart study. N Engl J Med. 2016;374:523–32. [DOI] [PubMed] [PMC]

21.

DeCarli C, Massaro J, Harvey D, Hald J, Tullberg M, Au R, et al. Measures of brain morphology and infarction in the framingham heart study: establishing what is normal. Neurobiol Aging. 2005;26:491–510. [DOI] [PubMed]

22.

Jefferson AL, Himali JJ, Beiser AS, Au R, Massaro JM, Seshadri S, et al. Cardiac index is associated with brain aging: the Framingham Heart Study. Circulation. 2010;122:690–7. [DOI] [PubMed] [PMC]

23.

DeCarli C, Reed T, Miller BL, Wolf PA, Swan GE, Carmelli D. Impact of apolipoprotein E epsilon4 and vascular disease on brain morphology in men from the NHLBI twin study. Stroke. 1999;30:1548–53. [DOI] [PubMed]

24.

Das RR, Seshadri S, Beiser AS, Kelly-Hayes M, Au R, Himali JJ, et al. Prevalence and correlates of silent cerebral infarcts in the Framingham offspring study. Stroke. 2008;39:2929–35. [DOI] [PubMed] [PMC]

25.

Romero JR, Beiser A, Himali JJ, Shoamanesh A, DeCarli C, Seshadri S. Cerebral microbleeds and risk of incident dementia: the Framingham Heart Study. Neurobiol Aging. 2017;54:94–9. [DOI] [PubMed] [PMC]

26.

DeCarli C, Miller BL, Swan GE, Reed T, Wolf PA, Garner J, et al. Predictors of brain morphology for the men of the NHLBI twin study. Stroke. 1999;30:529–36. [DOI] [PubMed]

27.

Aljabar P, Heckemann RA, Hammers A, Hajnal JV, Rueckert D. Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy. Neuroimage. 2009;46:726–38. [DOI] [PubMed]

28.

Rueckert D, Aljabar P, Heckemann RA, Hajnal JV, Hammers A. Diffeomorphic registration using B-splines. In: Larsen R, Nielsen M, Sporring J, editors. Medical image computing and computer-assisted intervention – MICCAI 2006. MICCAI 2006: Proceedings of the 9th International Conference; 2006 Oct 1–6; Copenhagen, Denmark. Berlin: Springer; 2006. pp. 702–9. [DOI] [PubMed]

29.

Kochunov P, Lancaster JL, Thompson P, Woods R, Mazziotta J, Hardies J, et al. Regional spatial normalization: toward an optimal target. J Comput Assist Tomogr. 2001;25:805–16. [DOI] [PubMed]

30.

Fletcher E, Carmichael O, Decarli C. MRI non-uniformity correction through interleaved bias estimation and B-spline deformation with a template. In: Engineering in medicine and biology society. EMBC 2012: Proceeding of the 2012 Annual International Conference of the IEEE; 2012 Aug 28–Sept 1; San Diego, USA. IEEE; 2012. pp. 106–9. [DOI] [PubMed] [PMC]

31.

Devlin B, Roeder K. Genomic control for association studies. Biometrics. 1999;55:997–1004. [DOI] [PubMed]

32.

Boughton AP, Welch RP, Flickinger M, VandeHaar P, Taliun D, Abecasis GR, et al. LocusZoom.js: interactive and embeddable visualization of genetic association study results. Bioinformatics. 2021;37:3017–8. [DOI] [PubMed] [PMC]

33.

GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45:580–5. [DOI] [PubMed] [PMC]

34.

Ng B, White CC, Klein HU, Sieberts SK, McCabe C, Patrick E, et al. An xQTL map integrates the genetic architecture of the human brain’s transcriptome and epigenome. Nat Neurosci. 2017;20:1418–26. [DOI] [PubMed] [PMC]

35.

Chojdak-Łukasiewicz J, Dziadkowiak E, Zimny A, Paradowski B. Cerebral small vessel disease: a review. Adv Clin Exp Med. 2021;30:349–56. [DOI] [PubMed]

36.

Kutikhin AG, Sinitsky MY, Yuzhalin AE, Velikanova EA. Shear stress: an essential driver of endothelial progenitor cells. J Mol Cell Cardiol. 2018;118:46–69. [DOI] [PubMed]

37.

Chen S, Li M, Sun J, Wang D, Weng C, Zeng Y, et al. Human umbilical cord blood-derived CD133⁺CD34⁺cells protect retinal endothelial cells and ganglion cells in X-irradiated rats through angioprotective and neurotrophic factors. Front Cell Dev Biol. 2022;10:801302. [DOI] [PubMed] [PMC]

38.

AbuSamra DB, Aleisa FA, Al-Amoodi AS, Jalal Ahmed HM, Chin CJ, Abuelela AF, et al. Not just a marker: CD34 on human hematopoietic stem/progenitor cells dominates vascular selectin binding along with CD44. Blood Adv. 2017;1:2799–816. [DOI] [PubMed] [PMC]

39.

Meregalli M, Farini A, Belicchi M, Torrente Y. CD133⁺ cells isolated from various sources and their role in future clinical perspectives. Expert Opin Biol Ther. 2010;10:1521–8. [DOI] [PubMed]

40.

Bigalke B, Schreitmüller B, Sopova K, Paul A, Stransky E, Gawaz M, et al. Adipocytokines and CD34⁺ progenitor cells in Alzheimer’s disease. PLoS One. 2011;6:e20286. [DOI] [PubMed] [PMC]

41.

Kalaria RN, Kroon SN. Expression of leukocyte antigen CD34 by brain capillaries in Alzheimer’s disease and neurologically normal subjects. Acta Neuropathol. 1992;84:606–12. [DOI] [PubMed]

42.

Torrente Y, Belicchi M, Sampaolesi M, Pisati F, Meregalli M, D’Antona G, et al. Human circulating AC133⁺ stem cells restore dystrophin expression and ameliorate function in dystrophic skeletal muscle. J Clin Invest. 2004;114:182–95. [DOI] [PubMed] [PMC]

43.

Agarwal N, Carare RO. Cerebral vessels: an overview of anatomy, physiology, and role in the drainage of fluids and solutes. Front Neurol. 2021;11:611485. [DOI] [PubMed] [PMC]

44.

Silva MVF, Loures CMG, Alves LCV, de Souza LC, Borges KBG, Carvalho MDG. Alzheimer’s disease: risk factors and potentially protective measures. J Biomed Sci. 2019;26:33. [DOI] [PubMed] [PMC]

45.

Untergasser G, Koeck R, Wolf D, Rumpold H, Ott H, Debbage P, et al. CD34⁺/CD133⁻ circulating endothelial precursor cells (CEP): characterization, senescence and in vivo application. Exp Gerontol. 2006;41:600–8. [DOI] [PubMed]

46.

Kapoor A, Gaubert A, Marshall A, Meier IB, Yew B, Ho JK, et al. Increased levels of circulating angiogenic cells and signaling proteins in older adults with cerebral small vessel disease. Front Aging Neurosci. 2021;13:711784. [DOI] [PubMed] [PMC]

47.

Huang ZX, Fang J, Zhou CH, Zeng J, Yang D, Liu Z. CD34⁺ cells and endothelial progenitor cell subpopulations are associated with cerebral small vessel disease burden. Biomark Med. 2021;15:191–200. [DOI] [PubMed]

48.

Taguchi A, Matsuyama T, Moriwaki H, Hayashi T, Hayashida K, Nagatsuka K, et al. Circulating CD34-positive cells provide an index of cerebrovascular function. Circulation. 2004;109:2972–5. [DOI] [PubMed]

49.

Dalkara T, Alarcon-Martinez L. Cerebral microvascular pericytes and neurogliovascular signaling in health and disease. Brain Res. 2015;1623:3–17. [DOI] [PubMed]

50.

Heiss C, Keymel S, Niesler U, Ziemann J, Kelm M, Kalka C. Impaired progenitor cell activity in age-related endothelial dysfunction. J Am Coll Cardiol. 2005;45:1441–8. [DOI] [PubMed]

51.

Povsic TJ, Zhou J, Adams SD, Bolognesi MP, Attarian DE, Peterson ED. Aging is not associated with bone marrow-resident progenitor cell depletion. J Gerontol A Biol Sci Med Sci. 2010;65A:1042–50. [DOI] [PubMed] [PMC]

52.

Madonna R, Ferdinandy P, De Caterina R, Willerson JT, Marian AJ. Recent developments in cardiovascular stem cells. Circ Res. 2014;115:e71–8. [DOI] [PubMed]

53.

Al Mheid I, Hayek SS, Ko YA, Akbik F, Li Q, Ghasemzadeh N, et al. Age and human regenerative capacity impact of cardiovascular risk factors. Circ Res. 2016;119:801–9. [DOI] [PubMed] [PMC]

54.

Povsic TJ, Sloane R, Green JB, Zhou J, Pieper CF, Pearson MP, et al. Depletion of circulating progenitor cells precedes overt diabetes: a substudy from the VA enhanced fitness trial. J Diabetes Complications. 2013;27:633–6. [DOI] [PubMed] [PMC]

55.

Povsic TJ, Sloane R, Pieper CF, Pearson MP, Peterson ED, Cohen HJ, et al. Endothelial progenitor cell levels predict future physical function: an exploratory analysis from the VA enhanced fitness study. J Gerontol A Biol Sci Med Sci. 2016;71:362–9. [DOI] [PubMed] [PMC]

56.

Topel ML, Hayek SS, Ko YA, Sandesara PB, Samman Tahhan A, Hesaroieh I, et al. Sex differences in circulating progenitor cells. J Am Heart Assoc. 2017;6:e006245. [DOI] [PubMed] [PMC]

57.

Tamir-Livne Y, Mubariki R, Bengal E. Adhesion molecule Kirrel3/Neph2 is required for the elongated shape of myocytes during skeletal muscle differentiation. Int J Dev Biol. 2017;61:337–45. [DOI] [PubMed]

58.

Martin EA, Muralidhar S, Wang Z, Cervantes DC, Basu R, Taylor MR, et al. Correction: The intellectual disability gene Kirrel3 regulates target-specific mossy fiber synapse development in the hippocampus. Elife. 2016;5:e18706. [DOI] [PubMed] [PMC]

59.

Ueno H, Sakita-Ishikawa M, Morikawa Y, Nakano T, Kitamura T, Saito M. A stromal cell-derived membrane protein that supports hematopoietic stem cells. Nat Immunol. 2003;4:457–63. [DOI] [PubMed]

60.

Khan Mu, Ali I, Jiao W, Wang Y, Masood S, Yousaf MZ, et al. Ex vivo expansion of functional human UCB-HSCs/HPCs by coculture with AFT024-hkirre cells. Biomed Res Int. 2014;2014:412075. [DOI] [PubMed] [PMC]

61.

Völker LA, Maar BA, Pulido Guevara BA, Bilkei-Gorzo A, Zimmer A, Brönneke H, et al. Neph2/Kirrel3 regulates sensory input, motor coordination, and home-cage activity in rodents. Genes Brain Behav. 2018;17:e12516. [DOI] [PubMed]

62.

Taylor MR, Martin EA, Sinnen B, Trilokekar R, Ranza E, Antonarakis SE, et al. Kirrel3-mediated synapse formation is attenuated by disease-associated missense variants. J Neurosci. 2020;40:5376–88. [DOI] [PubMed] [PMC]

63.

Baig DN, Yanagawa T, Tabuchi K. Distortion of the normal function of synaptic cell adhesion molecules by genetic variants as a risk for autism spectrum disorders. Brain Res Bull. 2017;129:82–90. [DOI] [PubMed]

64.

Mao Y, Tu R, Huang Y, Mao D, Yang Z, Lau PK, et al. The exocyst functions in niche cells to promote germline stem cell differentiation by directly controlling EGFR membrane trafficking. Development. 2019;146:dev174615. [DOI] [PubMed] [PMC]

65.

Sun J, Song F, Wang J, Han G, Bai Z, Xie B, et al. Hidden risk genes with high-order intragenic epistasis in Alzheimer’s disease. J Alzheimers Dis. 2014;41:1039–56. [DOI] [PubMed]

66.

Hatcher C, Relton CL, Gaunt TR, Richardson TG. Leveraging brain cortex-derived molecular data to elucidate epigenetic and transcriptomic drivers of complex traits and disease. Transl Psychiatry. 2019;9:105. [DOI] [PubMed] [PMC]

67.

Martin EA, Woodruff D, Rawson RL, Williams ME. Examining hippocampal mossy fiber synapses by 3D electron microscopy in wildtype and Kirrel3 knockout mice. eNeuro. 2017;4:ENEURO.0088-17.2017. [DOI] [PubMed] [PMC]

68.

Prince JE, Brignall AC, Cutforth T, Shen K, Cloutier JF. Kirrel3 is required for the coalescence of vomeronasal sensory neuron axons into glomeruli and for male-male aggression. Development. 2013;140:2398–408. [DOI] [PubMed] [PMC]

69.

Choi SY, Han K, Cutforth T, Chung W, Park H, Lee D, et al. Mice lacking the synaptic adhesion molecule Neph2/Kirrel3 display moderate hyperactivity and defective novel object preference. Front Cell Neurosci. 2015;9:283. [DOI] [PubMed] [PMC]

70.

Jiang S, Zhang CY, Tang L, Zhao LX, Chen HZ, Qiu Y. Integrated genomic analysis revealed associated genes for Alzheimer’s disease in APOE4 non-carriers. Curr Alzheimer Res. 2019;16:753–63. [DOI] [PubMed]

71.

Hisaoka T, Komori T, Kitamura T, Morikawa Y. Abnormal behaviours relevant to neurodevelopmental disorders in Kirrel3-knockout mice. Sci Rep. 2018;8:1408. [DOI] [PubMed] [PMC]

72.

Liu YF, Sowell SM, Luo Y, Chaubey A, Cameron RS, Kim HG, et al. Autism and intellectual disability-associated KIRREL3 interacts with neuronal proteins MAP1B and MYO16 with potential roles in neurodevelopment. PLoS One. 2015;10:e0123106. [DOI] [PubMed] [PMC]

73.

Bhalla K, Luo Y, Buchan T, Beachem MA, Guzauskas GF, Ladd S, et al. Alterations in CDH15 and KIRREL3 in patients with mild to severe intellectual disability. Am J Hum Genet. 2008;83:703–13. [DOI] [PubMed] [PMC]

74.

Ciaccio C, Leonardi E, Polli R, Murgia A, D’Arrigo S, Granocchio E, et al. A missense de novo variant in the CASK-interactor KIRREL3 gene leading to neurodevelopmental disorder with mild cerebellar hypoplasia. Neuropediatrics. 2021;52:484–8. [DOI] [PubMed]

75.

Anzick S, Thurm A, Burkett S, Velez D, Cho E, Chlebowski C, et al. Chromoanasynthesis as a cause of Jacobsen syndrome. Am J Med Genet A. 2020;182:2533–9. [DOI] [PubMed]

76.

Guerin A, Stavropoulos DJ, Diab Y, Chénier S, Christensen H, Kahr WH, et al. Interstitial deletion of 11q-implicating the KIRREL3 gene in the neurocognitive delay associated with Jacobsen syndrome. Am J Med Genet A. 2012;158A:2551–6. [DOI] [PubMed]

77.

Kalsner L, Twachtman-Bassett J, Tokarski K, Stanley C, Dumont-Mathieu T, Cotney J, et al. Genetic testing including targeted gene panel in a diverse clinical population of children with autism spectrum disorder: findings and implications. Mol Genet Genomic Med. 2018;6:171–85. [DOI] [PubMed] [PMC]

78.

Evers C, Maas B, Koch KA, Jauch A, Janssen JW, Sutter C, et al. Mosaic deletion of EXOC6B: further evidence for an important role of the exocyst complex in the pathogenesis of intellectual disability. Am J Med Genet A. 2014;164:3088–94. [DOI] [PubMed]

79.

Frühmesser A, Blake J, Haberlandt E, Baying B, Raeder B, Runz H, et al. Disruption of EXOC6B in a patient with developmental delay, epilepsy, and a de novo balanced t(2;8) translocation. Eur J Hum Genet. 2013;21:1177–80. [DOI] [PubMed] [PMC]

80.

Borsani G, Piovani G, Zoppi N, Bertini V, Bini R, Notarangelo L, et al. Cytogenetic and molecular characterization of a de-novo t(2p;7p) translocation involving TNS3 and EXOC6B genes in a boy with a complex syndromic phenotype. Eur J Med Genet. 2008;51:292–302. [DOI] [PubMed]

81.

Bjørklund G, Kern JK, Urbina MA, Saad K, El-Houfey AA, Geier DA, et al. Cerebral hypoperfusion in autism spectrum disorder. Acta Neurobiol Exp (Wars). 2018;78:21–9. [PubMed]