1
|
Bender RG, Sirota SB, Swetschinski LR, Dominguez RMV, Novotney A, Wool EE, Ikuta KS, Vongpradith A, Rogowski ELB, Doxey M, Troeger CE, Albertson SB, Ma J, He J, Maass KL, A.F.Simões E, Abdoun M, Abdul Aziz JM, Abdulah DM, Abu Rumeileh S, Abualruz H, Aburuz S, Adepoju AV, Adha R, Adikusuma W, Adra S, Afraz A, Aghamiri S, Agodi A, Ahmadzade AM, Ahmed H, Ahmed A, Akinosoglou K, AL-Ahdal TMA, Al-amer RM, Albashtawy M, AlBataineh MT, Alemi H, Al-Gheethi AAS, Ali A, Ali SSS, Alqahtani JS, AlQudah M, Al-Tawfiq JA, Al-Worafi YM, Alzoubi KH, Amani R, Amegbor PM, Ameyaw EK, Amuasi JH, Anil A, Anyanwu PE, Arafat M, Areda D, Arefnezhad R, Atalell KA, Ayele F, Azzam AY, Babamohamadi H, Babin FX, Bahurupi Y, Baker S, Banik B, Barchitta M, Barqawi HJ, Basharat Z, Baskaran P, Batra K, Batra R, Bayileyegn NS, Beloukas A, Berkley JA, Beyene KA, Bhargava A, Bhattacharjee P, Bielicki JA, Bilalaga MM, Bitra VR, Brown CS, Burkart K, Bustanji Y, Carr S, Chahine Y, Chattu VK, Chichagi F, Chopra H, Chukwu IS, Chung E, Dadana S, Dai X, Dandona L, Dandona R, Darban I, Dash NR, Dashti M, Dashtkoohi M, Dekker DM, Delgado-Enciso I, Devanbu VGC, Dhama K, Diao N, Do THP, Dokova KG, Dolecek C, Dziedzic AM, Eckmanns T, Ed-Dra A, Efendi F, Eftekharimehrabad A, Eyre DW, Fahim A, Feizkhah A, Felton TW, Ferreira N, Flor LS, Gaihre S, Gebregergis MW, Gebrehiwot M, Geffers C, Gerema U, Ghaffari K, Goldust M, Goleij P, Guan SY, Gudeta MD, Guo C, Gupta VB, Gupta I, Habibzadeh F, Hadi NR, Haeuser E, Hailu WB, Hajibeygi R, Haj-Mirzaian A, Haller S, Hamiduzzaman M, Hanifi N, Hansel J, Hasnain MS, Haubold J, Hoan NQ, Huynh HH, Iregbu KC, Islam MR, Jafarzadeh A, Jairoun AA, Jalili M, Jomehzadeh N, Joshua CE, Kabir MA, Kamal Z, Kanmodi KK, Kantar RS, Karimi Behnagh A, Kaur N, Kaur H, Khamesipour F, Khan MN, Khan suheb MZ, Khanal V, Khatab K, Khatib MN, Kim G, Kim K, Kitila ATT, Komaki S, Krishan K, Krumkamp R, Kuddus MA, Kurniasari MD, Lahariya C, Latifinaibin K, Le NHH, Le TTT, Le TDT, Lee SW, LEPAPE A, Lerango TL, Li MC, Mahboobipour AA, Malhotra K, Mallhi TH, Manoharan A, Martinez-Guerra BA, Mathioudakis AG, Mattiello R, May J, McManigal B, McPhail SM, Mekene Meto T, Mendez-Lopez MAM, Meo SA, Merati M, Mestrovic T, Mhlanga L, Minh LHN, Misganaw A, Mishra V, Misra AK, Mohamed NS, Mohammadi E, Mohammed M, Mohammed M, Mokdad AH, Monasta L, Moore CE, Motappa R, Mougin V, Mousavi P, Mulita F, Mulu AA, Naghavi P, Naik GR, Nainu F, Nair TS, Nargus S, Negaresh M, Nguyen HTH, Nguyen DH, Nguyen VT, Nikolouzakis TK, Noman EA, Nri-Ezedi CA, Odetokun IA, Okwute PG, Olana MD, Olanipekun TO, Olasupo OO, Olivas-Martinez A, Ordak M, Ortiz-Brizuela E, Ouyahia A, Padubidri JR, Pak A, Pandey A, Pantazopoulos I, Parija PP, Parikh RR, Park S, Parthasarathi A, Pashaei A, Peprah P, Pham HT, Poddighe D, Pollard A, Ponce-De-Leon A, Prakash PY, Prates EJS, Quan NK, Raee P, Rahim F, Rahman M, Rahmati M, Ramasamy SK, Ranjan S, Rao IR, Rashid AM, Rattanavong S, Ravikumar N, Reddy MMRK, Redwan EMM, Reiner RC, Reyes LF, Roberts T, Rodrigues M, Rosenthal VD, Roy P, Runghien T, Saeed U, Saghazadeh A, Saheb Sharif-Askari N, Saheb Sharif-Askari F, Sahoo SS, Sahu M, Sakshaug JW, Salami AA, Saleh MA, Salehi omran H, Sallam M, Samadzadeh S, Samodra YL, Sanjeev RK, Sarasmita MA, Saravanan A, Sartorius B, Saulam J, Schumacher AE, Seyedi SA, Shafie M, Shahid S, Sham S, Shamim MA, Shamshirgaran MA, Shastry RP, Sherchan SP, Shiferaw D, Shittu A, Siddig EE, Sinto R, Sood A, Sorensen RJD, Stergachis A, Stoeva TZ, Swain CK, Szarpak L, Tamuzi JL, Temsah MH, Tessema MBT, Thangaraju P, Tran NM, Tran NH, Tumurkhuu M, Ty SS, Udoakang AJ, Ulhaq I, Umar TP, Umer AA, Vahabi SM, Vaithinathan AG, Van den Eynde J, Walson JL, Waqas M, Xing Y, Yadav MK, Yahya G, Yon DK, Zahedi Bialvaei A, Zakham F, Zeleke AM, Zhai C, Zhang Z, Zhang H, Zielińska M, Zheng P, Aravkin AY, Vos T, Hay SI, Mosser JF, Lim SS, Naghavi M, Murray CJL, Kyu HH. Global, regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990-2021: a systematic analysis from the Global Burden of Disease Study 2021. Lancet Infect Dis 2024:S1473-3099(24)00176-2. [PMID: 38636536 DOI: 10.1016/s1473-3099(24)00176-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/19/2024] [Accepted: 03/07/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Lower respiratory infections (LRIs) are a major global contributor to morbidity and mortality. In 2020-21, non-pharmaceutical interventions associated with the COVID-19 pandemic reduced not only the transmission of SARS-CoV-2, but also the transmission of other LRI pathogens. Tracking LRI incidence and mortality, as well as the pathogens responsible, can guide health-system responses and funding priorities to reduce future burden. We present estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 of the burden of non-COVID-19 LRIs and corresponding aetiologies from 1990 to 2021, inclusive of pandemic effects on the incidence and mortality of select respiratory viruses, globally, regionally, and for 204 countries and territories. METHODS We estimated mortality, incidence, and aetiology attribution for LRI, defined by the GBD as pneumonia or bronchiolitis, not inclusive of COVID-19. We analysed 26 259 site-years of mortality data using the Cause of Death Ensemble model to estimate LRI mortality rates. We analysed all available age-specific and sex-specific data sources, including published literature identified by a systematic review, as well as household surveys, hospital admissions, health insurance claims, and LRI mortality estimates, to generate internally consistent estimates of incidence and prevalence using DisMod-MR 2.1. For aetiology estimation, we analysed multiple causes of death, vital registration, hospital discharge, microbial laboratory, and literature data using a network analysis model to produce the proportion of LRI deaths and episodes attributable to the following pathogens: Acinetobacter baumannii, Chlamydia spp, Enterobacter spp, Escherichia coli, fungi, group B streptococcus, Haemophilus influenzae, influenza viruses, Klebsiella pneumoniae, Legionella spp, Mycoplasma spp, polymicrobial infections, Pseudomonas aeruginosa, respiratory syncytial virus (RSV), Staphylococcus aureus, Streptococcus pneumoniae, and other viruses (ie, the aggregate of all viruses studied except influenza and RSV), as well as a residual category of other bacterial pathogens. FINDINGS Globally, in 2021, we estimated 344 million (95% uncertainty interval [UI] 325-364) incident episodes of LRI, or 4350 episodes (4120-4610) per 100 000 population, and 2·18 million deaths (1·98-2·36), or 27·7 deaths (25·1-29·9) per 100 000. 502 000 deaths (406 000-611 000) were in children younger than 5 years, among which 254 000 deaths (197 000-320 000) occurred in countries with a low Socio-demographic Index. Of the 18 modelled pathogen categories in 2021, S pneumoniae was responsible for the highest proportions of LRI episodes and deaths, with an estimated 97·9 million (92·1-104·0) episodes and 505 000 deaths (454 000-555 000) globally. The pathogens responsible for the second and third highest episode counts globally were other viral aetiologies (46·4 million [43·6-49·3] episodes) and Mycoplasma spp (25·3 million [23·5-27·2]), while those responsible for the second and third highest death counts were S aureus (424 000 [380 000-459 000]) and K pneumoniae (176 000 [158 000-194 000]). From 1990 to 2019, the global all-age non-COVID-19 LRI mortality rate declined by 41·7% (35·9-46·9), from 56·5 deaths (51·3-61·9) to 32·9 deaths (29·9-35·4) per 100 000. From 2019 to 2021, during the COVID-19 pandemic and implementation of associated non-pharmaceutical interventions, we estimated a 16·0% (13·1-18·6) decline in the global all-age non-COVID-19 LRI mortality rate, largely accounted for by a 71·8% (63·8-78·9) decline in the number of influenza deaths and a 66·7% (56·6-75·3) decline in the number of RSV deaths. INTERPRETATION Substantial progress has been made in reducing LRI mortality, but the burden remains high, especially in low-income and middle-income countries. During the COVID-19 pandemic, with its associated non-pharmaceutical interventions, global incident LRI cases and mortality attributable to influenza and RSV declined substantially. Expanding access to health-care services and vaccines, including S pneumoniae, H influenzae type B, and novel RSV vaccines, along with new low-cost interventions against S aureus, could mitigate the LRI burden and prevent transmission of LRI-causing pathogens. FUNDING Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care (UK).
Collapse
|
2
|
Steinmetz JD, Seeher KM, Schiess N, Nichols E, Cao B, Servili C, Cavallera V, Cousin E, Hagins H, Moberg ME, Mehlman ML, Abate YH, Abbas J, Abbasi MA, Abbasian M, Abbastabar H, Abdelmasseh M, Abdollahi M, Abdollahi M, Abdollahifar MA, Abd-Rabu R, Abdulah DM, Abdullahi A, Abedi A, Abedi V, Abeldaño Zuñiga RA, Abidi H, Abiodun O, Aboagye RG, Abolhassani H, Aboyans V, Abrha WA, Abualhasan A, Abu-Gharbieh E, Aburuz S, Adamu LH, Addo IY, Adebayo OM, Adekanmbi V, Adekiya TA, Adikusuma W, Adnani QES, Adra S, Afework T, Afolabi AA, Afraz A, Afzal S, Aghamiri S, Agodi A, Agyemang-Duah W, Ahinkorah BO, Ahmad A, Ahmad D, Ahmad S, Ahmadzade AM, Ahmed A, Ahmed A, Ahmed H, Ahmed JQ, Ahmed LA, Ahmed MB, Ahmed SA, Ajami M, Aji B, Ajumobi O, Akade SE, Akbari M, Akbarialiabad H, Akhlaghi S, Akinosoglou K, Akinyemi RO, Akonde M, Al Hasan SM, Alahdab F, AL-Ahdal TMA, Al-amer RM, Albashtawy M, AlBataineh MT, Aldawsari KA, Alemi H, Alemi S, Algammal AM, Al-Gheethi AAS, Alhalaiqa FAN, Alhassan RK, Ali A, Ali EA, Ali L, Ali MU, Ali MM, Ali R, Ali S, Ali SSS, Ali Z, Alif SM, Alimohamadi Y, Aliyi AA, Aljofan M, Aljunid SM, Alladi S, Almazan JU, Almustanyir S, Al-Omari B, Alqahtani JS, Alqasmi I, Alqutaibi AY, Al-Shahi Salman R, Altaany Z, Al-Tawfiq JA, Altirkawi KA, Alvis-Guzman N, Al-Worafi YM, Aly H, Aly S, Alzoubi KH, Amani R, Amindarolzarbi A, Amiri S, Amirzade-Iranaq MH, Amu H, Amugsi DA, Amusa GA, Amzat J, Ancuceanu R, Anderlini D, Anderson DB, Andrei CL, Androudi S, Angappan D, Angesom TW, Anil A, Ansari-Moghaddam A, Anwer R, Arafat M, Aravkin AY, Areda D, Ariffin H, Arifin H, Arkew M, Ärnlöv J, Arooj M, Artamonov AA, Artanti KD, Aruleba RT, Asadi-Pooya AA, Asena TF, Asghari-Jafarabadi M, Ashraf M, Ashraf T, Atalell KA, Athari SS, Atinafu BTT, Atorkey P, Atout MMW, Atreya A, Aujayeb A, Avan A, Ayala Quintanilla BP, Ayatollahi H, Ayinde OO, Ayyoubzadeh SM, Azadnajafabad S, Azizi Z, Azizian K, Azzam AY, Babaei M, Badar M, Badiye AD, Baghdadi S, Bagherieh S, Bai R, Baig AA, Balakrishnan S, Balalla S, Baltatu OC, Banach M, Bandyopadhyay S, Banerjee I, Baran MF, Barboza MA, Barchitta M, Bardhan M, Barker-Collo SL, Bärnighausen TW, Barrow A, Bashash D, Bashiri H, Bashiru HA, Basiru A, Basso JD, Basu S, Batiha AMM, Batra K, Baune BT, Bedi N, Begde A, Begum T, Behnam B, Behnoush AH, Beiranvand M, Béjot Y, Bekele A, Belete MA, Belgaumi UI, Bemanalizadeh M, Bender RG, Benfor B, Bennett DA, Bensenor IM, Berice B, Bettencourt PJG, Beyene KA, Bhadra A, Bhagat DS, Bhangdia K, Bhardwaj N, Bhardwaj P, Bhargava A, Bhaskar S, Bhat AN, Bhat V, Bhatti GK, Bhatti JS, Bhatti R, Bijani A, Bikbov B, Bilalaga MM, Biswas A, Bitaraf S, Bitra VR, Bjørge T, Bodolica V, Bodunrin AO, Boloor A, Braithwaite D, Brayne C, Brenner H, Briko A, Bringas Vega ML, Brown J, Budke CM, Buonsenso D, Burkart K, Burns RA, Bustanji Y, Butt MH, Butt NS, Butt ZA, Cabral LS, Caetano dos Santos FL, Calina D, Campos-Nonato IR, Cao C, Carabin H, Cárdenas R, Carreras G, Carvalho AF, Castañeda-Orjuela CA, Casulli A, Catalá-López F, Catapano AL, Caye A, Cegolon L, Cenderadewi M, Cerin E, Chacón-Uscamaita PRU, Chan JSK, Chanie GS, Charan J, Chattu VK, Chekol Abebe E, Chen H, Chen J, Chi G, Chichagi F, Chidambaram SB, Chimoriya R, Ching PR, Chitheer A, Chong YY, Chopra H, Choudhari SG, Chowdhury EK, Chowdhury R, Christensen H, Chu DT, Chukwu IS, Chung E, Coberly K, Columbus A, Comachio J, Conde J, Cortesi PA, Costa VM, Couto RAS, Criqui MH, Cruz-Martins N, Dabbagh Ohadi MA, Dadana S, Dadras O, Dai X, Dai Z, D'Amico E, Danawi HA, Dandona L, Dandona R, Darwish AH, Das S, Das S, Dascalu AM, Dash NR, Dashti M, De la Hoz FP, de la Torre-Luque A, De Leo D, Dean FE, Dehghan A, Dehghan A, Dejene H, Demant D, Demetriades AK, Demissie S, Deng X, Desai HD, Devanbu VGC, Dhama K, Dharmaratne SD, Dhimal M, Dias da Silva D, Diaz D, Dibas M, Ding DD, Dinu M, Dirac MA, Diress M, Do TC, Do THP, Doan KDK, Dodangeh M, Doheim MF, Dokova KG, Dongarwar D, Dsouza HL, Dube J, Duraisamy S, Durojaiye OC, Dutta S, Dziedzic AM, Edinur HA, Eissazade N, Ekholuenetale M, Ekundayo TC, El Nahas N, El Sayed I, Elahi Najafi MA, Elbarazi I, Elemam NM, Elgar FJ, Elgendy IY, Elhabashy HR, Elhadi M, Elilo LT, Ellenbogen RG, Elmeligy OAA, Elmonem MA, Elshaer M, Elsohaby I, Emamverdi M, Emeto TI, Endres M, Esezobor CI, Eskandarieh S, Fadaei A, Fagbamigbe AF, Fahim A, Faramarzi A, Fares J, Farjoud Kouhanjani M, Faro A, Farzadfar F, Fatehizadeh A, Fathi M, Fathi S, Fatima SAF, Feizkhah A, Fereshtehnejad SM, Ferrari AJ, Ferreira N, Fetensa G, Firouraghi N, Fischer F, Fonseca AC, Force LM, Fornari A, Foroutan B, Fukumoto T, Gadanya MA, Gaidhane AM, Galali Y, Galehdar N, Gan Q, Gandhi AP, Ganesan B, Gardner WM, Garg N, Gau SY, Gautam RK, Gebre T, Gebrehiwot M, Gebremeskel GG, Gebreslassie HG, Getacher L, Ghaderi Yazdi B, Ghadirian F, Ghaffarpasand F, Ghanbari R, Ghasemi M, Ghazy RM, Ghimire S, Gholami A, Gholamrezanezhad A, Ghotbi E, Ghozy S, Gialluisi A, Gill PS, Glasstetter LM, Gnedovskaya EV, Golchin A, Golechha M, Goleij P, Golinelli D, Gomes-Neto M, Goulart AC, Goyal A, Gray RJ, Grivna M, Guadie HA, Guan B, Guarducci G, Guicciardi S, Gunawardane DA, Guo H, Gupta B, Gupta R, Gupta S, Gupta VB, Gupta VK, Gutiérrez RA, Habibzadeh F, Hachinski V, Haddadi R, Hadei M, Hadi NR, Haep N, Haile TG, Haj-Mirzaian A, Hall BJ, Halwani R, Hameed S, Hamiduzzaman M, Hammoud A, Han H, Hanifi N, Hankey GJ, Hannan MA, Hao J, Harapan H, Hareru HE, Hargono A, Harlianto NI, Haro JM, Hartman NN, Hasaballah AI, Hasan F, Hasani H, Hasanian M, Hassan A, Hassan S, Hassanipour S, Hassankhani H, Hassen MB, Haubold J, Hay SI, Hayat K, Hegazy MI, Heidari G, Heidari M, Heidari-Soureshjani R, Hesami H, Hezam K, Hiraike Y, Hoffman HJ, Holla R, Hopf KP, Horita N, Hossain MM, Hossain MB, Hossain S, Hosseinzadeh H, Hosseinzadeh M, Hostiuc S, Hu C, Huang J, Huda MN, Hussain J, Hussein NR, Huynh HH, Hwang BF, Ibitoye SE, Ilaghi M, Ilesanmi OS, Ilic IM, Ilic MD, Immurana M, Iravanpour F, Islam SMS, Ismail F, Iso H, Isola G, Iwagami M, Iwu CCD, Iyer M, Jaan A, Jacob L, Jadidi-Niaragh F, Jafari M, Jafarinia M, Jafarzadeh A, Jahankhani K, Jahanmehr N, Jahrami H, Jaiswal A, Jakovljevic M, Jamora RDG, Jana S, Javadi N, Javed S, Javeed S, Jayapal SK, Jayaram S, Jiang H, Johnson CO, Johnson WD, Jokar M, Jonas JB, Joseph A, Joseph N, Joshua CE, Jürisson M, Kabir A, Kabir Z, Kabito GG, Kadashetti V, Kafi F, Kalani R, Kalantar F, Kaliyadan F, Kamath A, Kamath S, Kanchan T, Kandel A, Kandel H, Kanmodi KK, Karajizadeh M, Karami J, Karanth SD, Karaye IM, Karch A, Karimi A, Karimi H, Karimi Behnagh A, Kasraei H, Kassebaum NJ, Kauppila JH, Kaur H, Kaur N, Kayode GA, Kazemi F, Keikavoosi-Arani L, Keller C, Keykhaei M, Khadembashiri MA, Khader YS, Khafaie MA, Khajuria H, Khalaji A, Khamesipour F, Khammarnia M, Khan M, Khan MAB, Khan YH, Khan Suheb MZ, Khanmohammadi S, Khanna T, Khatab K, Khatatbeh H, Khatatbeh MM, Khateri S, Khatib MN, Khayat Kashani HR, Khonji MS, khorashadizadeh F, Khormali M, Khubchandani J, Kian S, Kim G, Kim J, Kim MS, Kim YJ, Kimokoti RW, Kisa A, Kisa S, Kivimäki M, Kochhar S, Kolahi AA, Koly KN, Kompani F, Koroshetz WJ, Kosen S, Kourosh Arami M, Koyanagi A, Kravchenko MA, Krishan K, Krishnamoorthy V, Kuate Defo B, Kuddus MA, Kumar A, Kumar GA, Kumar M, Kumar N, Kumsa NB, Kundu S, Kurniasari MD, Kusuma D, Kuttikkattu A, Kyu HH, La Vecchia C, Ladan MA, Lahariya C, Laksono T, Lal DK, Lallukka T, Lám J, Lami FH, Landires I, Langguth B, Lasrado S, Latief K, Latifinaibin K, Lau KMM, Laurens MB, Lawal BK, Le LKD, Le TTT, Ledda C, Lee M, Lee SW, Lee SW, Lee WC, Lee YH, Leonardi M, Lerango TL, Li MC, Li W, Ligade VS, Lim SS, Linehan C, Liu C, Liu J, Liu W, Lo CH, Lo WD, Lobo SW, Logroscino G, Lopes G, Lopukhov PD, Lorenzovici L, Lorkowski S, Loureiro JA, Lubinda J, Lucchetti G, Lutzky Saute R, Ma ZF, Mabrok M, Machoy M, Madadizadeh F, Magdy Abd El Razek M, Maghazachi AA, Maghbouli N, Mahjoub S, Mahmoudi M, Majeed A, Malagón-Rojas JN, Malakan Rad E, Malhotra K, Malik AA, Malik I, Mallhi TH, Malta DC, Manilal A, Mansouri V, Mansournia MA, Marasini BP, Marateb HR, Maroufi SF, Martinez-Raga J, Martini S, Martins-Melo FR, Martorell M, März W, Marzo RR, Massano J, Mathangasinghe Y, Mathews E, Maude RJ, Maugeri A, Maulik PK, Mayeli M, Mazaheri M, McAlinden C, McGrath JJ, Meena JK, Mehndiratta MM, Mendez-Lopez MAM, Mendoza W, Mendoza-Cano O, Menezes RG, Merati M, Meretoja A, Merkin A, Mersha AM, Mestrovic T, Mi T, Miazgowski T, Michalek IM, Mihretie ET, Minh LHN, Mirfakhraie R, Mirica A, Mirrakhimov EM, Mirzaei M, Misganaw A, Misra S, Mithra P, Mizana BA, Mohamadkhani A, Mohamed NS, Mohammadi E, Mohammadi H, Mohammadi S, Mohammadi S, Mohammadshahi M, Mohammed M, Mohammed S, Mohammed S, Mohan S, Mojiri-forushani H, Moka N, Mokdad AH, Molinaro S, Möller H, Monasta L, Moniruzzaman M, Montazeri F, Moradi M, Moradi Y, Moradi-Lakeh M, Moraga P, Morovatdar N, Morrison SD, Mosapour A, Mosser JF, Mossialos E, Motaghinejad M, Mousavi P, Mousavi SE, Mubarik S, Muccioli L, Mughal F, Mukoro GD, Mulita A, Mulita F, Musaigwa F, Mustafa A, Mustafa G, Muthu S, Nagarajan AJ, Naghavi P, Naik GR, Nainu F, Nair TS, Najmuldeen HHR, Nakhostin Ansari N, Nambi G, Namdar Areshtanab H, Nargus S, Nascimento BR, Naser AY, Nashwan AJJ, Nasoori H, Nasreldein A, Natto ZS, Nauman J, Nayak BP, Nazri-Panjaki A, Negaresh M, Negash H, Negoi I, Negoi RI, Negru SM, Nejadghaderi SA, Nematollahi MH, Nesbit OD, Newton CRJ, Nguyen DH, Nguyen HTH, Nguyen HQ, Nguyen NTT, Nguyen PT, Nguyen VT, Niazi RK, Nikolouzakis TK, Niranjan V, Nnyanzi LA, Noman EA, Noroozi N, Norrving B, Noubiap JJ, Nri-Ezedi CA, Ntaios G, Nuñez-Samudio V, Nurrika D, Oancea B, Odetokun IA, O'Donnell MJ, Ogunsakin RE, Oguta JO, Oh IH, Okati-Aliabad H, Okeke SR, Okekunle AP, Okonji OC, Okwute PG, Olagunju AT, Olaiya MT, Olana MD, Olatubi MI, Oliveira GMM, Olufadewa II, Olusanya BO, Omar Bali A, Ong S, Onwujekwe OE, Ordak M, Orji AU, Ortega-Altamirano DV, Osuagwu UL, Otstavnov N, Otstavnov SS, Ouyahia A, Owolabi MO, P A MP, Pacheco-Barrios K, Padubidri JR, Pal PK, Palange PN, Palladino C, Palladino R, Palma-Alvarez RF, Pan F, Panagiotakos D, Panda-Jonas S, Pandey A, Pandey A, Pandian JD, Pangaribuan HU, Pantazopoulos I, Pardhan S, Parija PP, Parikh RR, Park S, Parthasarathi A, Pashaei A, Patel J, Patil S, Patoulias D, Pawar S, Pedersini P, Pensato U, Pereira DM, Pereira J, Pereira MO, Peres MFP, Perico N, Perna S, Petcu IR, Petermann-Rocha FE, Pham HT, Phillips MR, Pinilla-Monsalve GD, Piradov MA, Plotnikov E, Poddighe D, Polat B, Poluru R, Pond CD, Poudel GR, Pouramini A, Pourbagher-Shahri AM, Pourfridoni M, Pourtaheri N, Prakash PY, Prakash S, Prakash V, Prates EJS, Pritchett N, Purnobasuki H, Qasim NH, Qattea I, Qian G, Radhakrishnan V, Raee P, Raeisi Shahraki H, Rafique I, Raggi A, Raghav PR, Rahati MM, Rahim F, Rahimi Z, Rahimifard M, Rahman MO, Rahman MHU, Rahman M, Rahman MA, Rahmani AM, Rahmani S, Rahmani Youshanlouei H, Rahmati M, Raj Moolambally S, Rajabpour-Sanati A, Ramadan H, Ramasamy SK, Ramasubramani P, Ramazanu S, Rancic N, Rao IR, Rao SJ, Rapaka D, Rashedi V, Rashid AM, Rashidi MM, Rashidi Alavijeh M, Rasouli-Saravani A, Rawaf S, Razo C, Redwan EMM, Rekabi Bana A, Remuzzi G, Rezaei N, Rezaei N, Rezaei N, Rezaeian M, Rhee TG, Riad A, Robinson SR, Rodrigues M, Rodriguez JAB, Roever L, Rogowski ELB, Romoli M, Ronfani L, Roy P, Roy Pramanik K, Rubagotti E, Ruiz MA, Russ TC, S Sunnerhagen K, Saad AMA, Saadatian Z, Saber K, SaberiKamarposhti M, Sacco S, Saddik B, Sadeghi E, Sadeghian S, Saeed U, Saeed U, Safdarian M, Safi SZ, Sagar R, Sagoe D, Saheb Sharif-Askari F, Saheb Sharif-Askari N, Sahebkar A, Sahoo SS, Sahraian MA, Sajedi SA, Sakshaug JW, Saleh MA, Salehi Omran H, Salem MR, Salimi S, Samadi Kafil H, Samadzadeh S, Samargandy S, Samodra YL, Samuel VP, Samy AM, Sanadgol N, Sanjeev RK, Sanmarchi F, Santomauro DF, Santri IN, Santric-Milicevic MM, Saravanan A, Sarveazad A, Satpathy M, Saylan M, Sayyah M, Scarmeas N, Schlaich MP, Schuermans A, Schwarzinger M, Schwebel DC, Selvaraj S, Sendekie AK, Sengupta P, Senthilkumaran S, Serban D, Sergindo MT, Sethi Y, SeyedAlinaghi S, Seylani A, Shabani M, Shabany M, Shafie M, Shahabi S, Shahbandi A, Shahid S, Shahraki-Sanavi F, Shahsavari HR, Shahwan MJ, Shaikh MA, Shaji KS, Sham S, Shama ATT, Shamim MA, Shams-Beyranvand M, Shamsi MA, Shanawaz M, Sharath M, Sharfaei S, Sharifan A, Sharma M, Sharma R, Shashamo BB, Shayan M, Sheikhi RA, Shekhar S, Shen J, Shenoy SM, Shetty PH, Shiferaw DS, Shigematsu M, Shiri R, Shittu A, Shivakumar KM, Shokri F, Shool S, Shorofi SA, Shrestha S, Siankam Tankwanchi AB, Siddig EE, Sigfusdottir ID, Silva JP, Silva LMLR, Sinaei E, Singh BB, Singh G, Singh P, Singh S, Sirota SB, Sivakumar S, Sohag AAM, Solanki R, Soleimani H, Solikhah S, Solomon Y, Solomon Y, Song S, Song Y, Sotoudeh H, Spartalis M, Stark BA, Starnes JR, Starodubova AV, Stein DJ, Steiner TJ, Stovner LJ, Suleman M, Suliankatchi Abdulkader R, Sultana A, Sun J, Sunkersing D, Sunny A, Susianti H, Swain CK, Szeto MD, Tabarés-Seisdedos R, Tabatabaei SM, Tabatabai S, Tabish M, Taheri M, Tahvildari A, Tajbakhsh A, Tampa M, Tamuzi JJLL, Tan KK, Tang H, Tareke M, Tarigan IU, Tat NY, Tat VY, Tavakoli Oliaee R, Tavangar SM, Tavasol A, Tefera YM, Tehrani-Banihashemi A, Temesgen WA, Temsah MH, Teramoto M, Tesfaye AH, Tesfaye EG, Tesler R, Thakali O, Thangaraju P, Thapa R, Thapar R, Thomas NK, Thrift AG, Ticoalu JHV, Tillawi T, Toghroli R, Tonelli M, Tovani-Palone MR, Traini E, Tran NM, Tran NH, Tran PV, Tromans SJ, Truelsen TC, Truyen TTTT, Tsatsakis A, Tsegay GM, Tsermpini EE, Tualeka AR, Tufa DG, Ubah CS, Udoakang AJ, Ulhaq I, Umair M, Umakanthan S, Umapathi KK, Unim B, Unnikrishnan B, Vaithinathan AG, Vakilian A, Valadan Tahbaz S, Valizadeh R, Van den Eynde J, Vart P, Varthya SB, Vasankari TJ, Vaziri S, Vellingiri B, Venketasubramanian N, Verras GI, Vervoort D, Villafañe JH, Villani L, Vinueza Veloz AF, Viskadourou M, Vladimirov SK, Vlassov V, Volovat SR, Vu LT, Vujcic IS, Wagaye B, Waheed Y, Wahood W, Walde MT, Wang F, Wang S, Wang Y, Wang YP, Waqas M, Waris A, Weerakoon KG, Weintraub RG, Weldemariam AH, Westerman R, Whisnant JL, Wickramasinghe DP, Wickramasinghe ND, Willekens B, Wilner LB, Winkler AS, Wolfe CDA, Wu AM, Wulf Hanson S, Xu S, Xu X, Yadollahpour A, Yaghoubi S, Yahya G, Yamagishi K, Yang L, Yano Y, Yao Y, Yehualashet SS, Yeshaneh A, Yesiltepe M, Yi S, Yiğit A, Yiğit V, Yon DK, Yonemoto N, You Y, Younis MZ, Yu C, Yusuf H, Zadey S, Zahedi M, Zakham F, Zaki N, Zali A, Zamagni G, Zand R, Zandieh GGZ, Zangiabadian M, Zarghami A, Zastrozhin MS, Zeariya MGM, Zegeye ZB, Zeukeng F, Zhai C, Zhang C, Zhang H, Zhang Y, Zhang ZJ, Zhao H, Zhao Y, Zheng P, Zhou H, Zhu B, Zhumagaliuly A, Zielińska M, Zikarg YT, Zoladl M, Murray CJL, Ong KL, Feigin VL, Vos T, Dua T. Global, regional, and national burden of disorders affecting the nervous system, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Neurol 2024; 23:344-381. [PMID: 38493795 PMCID: PMC10949203 DOI: 10.1016/s1474-4422(24)00038-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 03/19/2024]
Abstract
BACKGROUND Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. METHODS We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. FINDINGS Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378-521), affecting 3·40 billion (3·20-3·62) individuals (43·1%, 40·5-45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7-26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6-38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5-32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7-2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. INTERPRETATION As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed. FUNDING Bill & Melinda Gates Foundation.
Collapse
|
3
|
Schumacher AE, Kyu HH, Aali A, Abbafati C, Abbas J, Abbasgholizadeh R, Abbasi MA, Abbasian M, Abd ElHafeez S, Abdelmasseh M, Abd-Elsalam S, Abdelwahab A, Abdollahi M, Abdoun M, Abdullahi A, Abdurehman AM, Abebe M, Abedi A, Abedi A, Abegaz TM, Abeldaño Zuñiga RA, Abhilash ES, Abiodun OO, Aboagye RG, Abolhassani H, Abouzid M, Abreu LG, Abrha WA, Abrigo MRM, Abtahi D, Abu Rumeileh S, Abu-Rmeileh NME, Aburuz S, Abu-Zaid A, Acuna JM, Adair T, Addo IY, Adebayo OM, Adegboye OA, Adekanmbi V, Aden B, Adepoju AV, Adetunji CO, Adeyeoluwa TE, Adeyomoye OI, Adha R, Adibi A, Adikusuma W, Adnani QES, Adra S, Afework A, Afolabi AA, Afraz A, Afyouni S, Afzal S, Agasthi P, Aghamiri S, Agodi A, Agyemang-Duah W, Ahinkorah BO, Ahmad A, Ahmad D, Ahmad F, Ahmad MM, Ahmad T, Ahmadi K, Ahmadzade AM, Ahmadzade M, Ahmed A, Ahmed H, Ahmed LA, Ahmed MB, Ahmed SA, Ajami M, Aji B, Ajumobi O, Akalu GT, Akara EM, Akinosoglou K, Akkala S, Akyirem S, Al Hamad H, Al Hasan SM, Al Homsi A, Al Qadire M, Ala M, Aladelusi TO, AL-Ahdal TMA, Alalalmeh SO, Al-Aly Z, Alam K, Alam M, Alam Z, Al-amer RM, Alanezi FM, Alanzi TM, Albashtawy M, AlBataineh MT, Aldridge RW, Alemi S, Al-Eyadhy A, Al-Gheethi AAS, Alhabib KF, Alhalaiqa FAN, Al-Hanawi MK, Ali A, Ali A, Ali BA, Ali H, Ali MU, Ali R, Ali SSS, Ali Z, Alian Samakkhah S, Alicandro G, Alif SM, Aligol M, Alimi R, Aliyi AA, Al-Jumaily A, Aljunid SM, Almahmeed W, Al-Marwani S, Al-Maweri SAA, Almazan JU, Al-Mekhlafi HM, Almidani O, Alomari MA, Alonso N, Alqahtani JS, Alqutaibi AY, Al-Sabah SK, Altaf A, Al-Tawfiq JA, Altirkawi KA, Alvi FJ, Alwafi H, Al-Worafi YM, Aly H, Alzoubi KH, Amare AT, Ameyaw EK, Amhare AF, Amin TT, Amindarolzarbi A, Aminian Dehkordi J, Amiri S, Amu H, Amugsi DA, Amzat J, Ancuceanu R, Anderlini D, Andrade PP, Andrei CL, Andrei T, Angappan D, Anil A, Anjum A, Antony CM, Antriyandarti E, Anuoluwa IA, Anwar SL, Anyasodor AE, Appiah SCY, Aqeel M, Arabloo J, Arabzadeh Bahri R, Arab-Zozani M, Arafat M, Araújo AM, Aravkin AY, Aremu A, Ariffin H, Aripov T, Armocida B, Arooj M, Artamonov AA, Artanti KD, Arulappan J, Aruleba IT, Aruleba RT, Arumugam A, Asaad M, Asgary S, Ashemo MY, Ashraf M, Asika MO, Athari SS, Atout MMW, Atreya A, Attia S, Aujayeb A, Avan A, Awotidebe AW, Ayala Quintanilla BP, Ayanore MA, Ayele GM, Ayuso-Mateos JL, Ayyoubzadeh SM, Azadnajafabad S, Azhar GS, Aziz S, Azzam AY, Babashahi M, Babu AS, Badar M, Badawi A, Badiye AD, Baghdadi S, Bagheri N, Bagherieh S, Bah S, Bahadorikhalili S, Bai J, Bai R, Baker JL, Bakkannavar SM, Bako AT, Balakrishnan S, Balogun SA, Baltatu OC, Bam K, Banach M, Bandyopadhyay S, Banik B, Banik PC, Bansal H, Barati S, Barchitta M, Bardhan M, Barker-Collo SL, Barone-Adesi F, Barqawi HJ, Barr RD, Barrero LH, Basharat Z, Bashir AIJ, Bashiru HA, Baskaran P, Basnyat B, Bassat Q, Basso JD, Basu S, Batra K, Batra R, Baune BT, Bayati M, Bayileyegn NS, Beaney T, Bedi N, Begum T, Behboudi E, Behnoush AH, Beiranvand M, Bejarano Ramirez DF, Belgaumi UI, Bell ML, Bello AK, Bello MB, Bello OO, Belo L, Beloukas A, Bendak S, Bennett DA, Bensenor IM, Benzian H, Berezvai Z, Berman AE, Bermudez ANC, Bettencourt PJG, Beyene HB, Beyene KA, Bhagat DS, Bhagavathula AS, Bhala N, Bhalla A, Bhandari D, Bhardwaj N, Bhardwaj P, Bhardwaj PV, Bhargava A, Bhaskar S, Bhat V, Bhatti GK, Bhatti JS, Bhatti MS, Bhatti R, Bhutta ZA, Bikbov B, Binmadi N, Bintoro BS, Biondi A, Bisignano C, Bisulli F, Biswas A, Biswas RK, Bitaraf S, Bjørge T, Bleyer A, Boampong MS, Bodolica V, Bodunrin AO, Bolarinwa OA, Bonakdar Hashemi M, Bonny A, Bora K, Bora Basara B, Borodo SB, Borschmann R, Botero Carvajal A, Bouaoud S, Boudalia S, Boyko EJ, Bragazzi NL, Braithwaite D, Brenner H, Britton G, Browne AJ, Brunoni AR, Bulamu NB, Bulto LN, Buonsenso D, Burkart K, Burns RA, Burugina Nagaraja S, Busse R, Bustanji Y, Butt ZA, Caetano dos Santos FL, Cai T, Calina D, Cámera LA, Campos LA, Campos-Nonato IR, Cao C, Cardenas CA, Cárdenas R, Carr S, Carreras G, Carrero JJ, Carugno A, Carvalho F, Carvalho M, Castaldelli-Maia JM, Castañeda-Orjuela CA, Castelpietra G, Catalá-López F, Catapano AL, Cattaruzza MS, Caye A, Cederroth CR, Cembranel F, Cenderadewi M, Cercy KM, Cerin E, Cevik M, Chacón-Uscamaita PRU, Chahine Y, Chakraborty C, Chan JSK, Chang CK, Charalampous P, Charan J, Chattu VK, Chatzimavridou-Grigoriadou V, Chavula MP, Cheema HA, Chen AT, Chen H, Chen L, Chen MX, Chen S, Cherbuin N, Chew DS, Chi G, Chirinos-Caceres JL, Chitheer A, Cho SMJ, Cho WCS, Chong B, Chopra H, Choudhary R, Chowdhury R, Chu DT, Chukwu IS, Chung E, Chung E, Chung SC, Cini KI, Clark CCT, Coberly K, Columbus A, Comfort H, Conde J, Conti S, Cortesi PA, Costa VM, Cousin E, Cowden RG, Criqui MH, Cruz-Martins N, Culbreth GT, Cullen P, Cunningham M, da Silva e Silva D, Dadana S, Dadras O, Dai Z, Dalal K, Dalli LL, Damiani G, D'Amico E, Daneshvar S, Darwesh AM, Das JK, Das S, Dash NR, Dashti M, Dávila-Cervantes CA, Davis Weaver N, Davletov K, De Leo D, Debele AT, Degenhardt L, Dehbandi R, Deitesfeld L, Delgado-Enciso I, Delgado-Ortiz L, Demant D, Demessa BH, Demetriades AK, Deng X, Denova-Gutiérrez E, Deribe K, Dervenis N, Des Jarlais DC, Desai HD, Desai R, Deuba K, Devanbu VGC, Dey S, Dhali A, Dhama K, Dhimal ML, Dhimal M, Dhingra S, Dias da Silva D, Diaz D, Dima A, Ding DD, Dirac MA, Dixit A, Dixit SG, Do TC, Do THP, do Prado CB, Dodangeh M, Dokova KG, Dolecek C, Dorsey ER, dos Santos WM, Doshi R, Doshmangir L, Douiri A, Dowou RK, Driscoll TR, Dsouza HL, Dube J, Dumith SC, Dunachie SJ, Duncan BB, Duraes AR, Duraisamy S, Durojaiye OC, Dutta S, Dzianach PA, Dziedzic AM, Ebenezer O, Eboreime E, Ebrahimi A, Echieh CP, Ed-Dra A, Edinur HA, Edvardsson D, Edvardsson K, Efendi D, Efendi F, Eghdami S, Eikemo TA, Eini E, Ekholuenetale M, Ekpor E, Ekundayo TC, El Arab RA, El Morsi DAW, El Sayed Zaki M, El Tantawi M, Elbarazi I, Elemam NM, Elgar FJ, Elgendy IY, ElGohary GMT, Elhabashy HR, Elhadi M, Elmeligy OAA, Elshaer M, Elsohaby I, Emami Zeydi A, Emamverdi M, Emeto TI, Engelbert Bain L, Erkhembayar R, Eshetie TC, Eskandarieh S, Espinosa-Montero J, Estep K, Etaee F, Eze UA, Fabin N, Fadaka AO, Fagbamigbe AF, Fahimi S, Falzone L, Farinha CSES, Faris MEM, Farjoud Kouhanjani M, Faro A, Farrokhpour H, Fatehizadeh A, Fattahi H, Fauk NK, Fazeli P, Feigin VL, Fekadu G, Fereshtehnejad SM, Feroze AH, Ferrante D, Ferrara P, Ferreira N, Fetensa G, Filip I, Fischer F, Flavel J, Flaxman AD, Flor LS, Florin BT, Folayan MO, Foley KM, Fomenkov AA, Force LM, Fornari C, Foroutan B, Foschi M, Francis KL, Franklin RC, Freitas A, Friedman J, Friedman SD, Fukumoto T, Fuller JE, Gaal PA, Gadanya MA, Gaihre S, Gaipov A, Gakidou E, Galali Y, Galehdar N, Gallus S, Gan Q, Gandhi AP, Ganesan B, Garg J, Gau SY, Gautam P, Gautam RK, Gazzelloni F, Gebregergis MW, Gebrehiwot M, Gebremariam TB, Gerema U, Getachew ME, Getachew T, Gething PW, Ghafourifard M, Ghahramani S, Ghailan KY, Ghajar A, Ghanbarnia MJ, Ghasemi M, Ghasemzadeh A, Ghassemi F, Ghazy RM, Ghimire S, Gholamian A, Gholamrezanezhad A, Ghorbani Vajargah P, Ghozali G, Ghozy S, Ghuge AD, Gialluisi A, Gibson RM, Gil AU, Gill PS, Gill TK, Gillum RF, Ginindza TG, Girmay A, Glasbey JC, Gnedovskaya EV, Göbölös L, Goel A, Goldust M, Golechha M, Goleij P, Golestanfar A, Golinelli D, Gona PN, Goudarzi H, Goudarzian AH, Goyal A, Greenhalgh S, Grivna M, Guarducci G, Gubari MIM, Gudeta MD, Guha A, Guicciardi S, Gunawardane DA, Gunturu S, Guo C, Gupta AK, Gupta B, Gupta IR, Gupta RD, Gupta S, Gupta VB, Gupta VK, Gupta VK, Gutiérrez RA, Habibzadeh F, Habibzadeh P, Hachinski V, Haddadi M, Haddadi R, Haep N, Hajj Ali A, Halboub ES, Halim SA, Hall BJ, Haller S, Halwani R, Hamadeh RR, Hamagharib Abdullah K, Hamidi S, Hamiduzzaman M, Hammoud A, Hanifi N, Hankey GJ, Hannan MA, Haque MN, Harapan H, Haro JM, Hasaballah AI, Hasan F, Hasan I, Hasan MT, Hasani H, Hasanian M, Hasanpour- Dehkordi A, Hassan AM, Hassan A, Hassanian-Moghaddam H, Hassanipour S, Haubold J, Havmoeller RJ, Hay SI, Hbid Y, Hebert JJ, Hegazi OE, Heidari G, Heidari M, Heidari-Foroozan M, Heidari-Soureshjani R, Helfer B, Herteliu C, Hesami H, Hettiarachchi D, Heyi DZ, Hezam K, Hiraike Y, Hoffman HJ, Holla R, Horita N, Hossain MB, Hossain MM, Hossain S, Hosseini MS, Hosseinzadeh H, Hosseinzadeh M, Hostiuc M, Hostiuc S, Hsairi M, Hsieh VCR, Hu C, Huang J, Huda MN, Hugo FN, Hultström M, Hussain J, Hussain S, Hussein NR, Huy LD, Huynh HH, Hwang BF, Ibitoye SE, Idowu OO, Ijo D, Ikuta KS, Ilaghi M, Ilesanmi OS, Ilic IM, Ilic MD, Immurana M, Inbaraj LR, Iradukunda A, Iravanpour F, Iregbu KC, Islam MR, Islam MM, Islam SMS, Islami F, Ismail NE, Isola G, Iwagami M, Iwu CCD, Iwu-Jaja CJ, Iyer M, J LM, Jaafari J, Jacob L, Jacobsen KH, Jadidi-Niaragh F, Jafarinia M, Jaggi K, Jahankhani K, Jahanmehr N, Jahrami H, Jain A, Jain N, Jairoun AA, Jakovljevic M, Jalilzadeh Yengejeh R, Jamshidi E, Jani CT, Janko MM, Jatau AI, Jayapal SK, Jayaram S, Jeganathan J, Jema AT, Jemere DM, Jeong W, Jha AK, Jha RP, Ji JS, Jiang H, Jin Y, Jin Y, Johnson O, Jomehzadeh N, Jones DP, Joo T, Joseph A, Joseph N, Joshua CE, Jozwiak JJ, Jürisson M, Kaambwa B, Kabir A, Kabir H, Kabir Z, Kadashetti V, Kahe F, Kakodkar PV, Kalani R, Kalankesh LR, Kaliyadan F, Kalra S, Kamath A, Kamireddy A, Kanagasabai T, Kandel H, Kanmiki EW, Kanmodi KK, Kantar RS, Kapoor N, Karajizadeh M, Karami Matin B, Karanth SD, Karaye IM, Karim A, Karimi H, Karimi SE, Karimi Behnagh A, Karkhah S, Karna AK, Kashoo FZ, Kasraei H, Kassaw NA, Kassebaum NJ, Kassel MB, Katamreddy A, Katikireddi SV, Katoto PDMC, Kauppila JH, Kaur N, Kaydi N, Kayibanda JF, Kayode GA, Kazemi F, Kazemian S, Kazeminia S, Keikavoosi-Arani L, Keller C, Kempen JH, Kerr JA, Kesse-Guyot E, Keykhaei M, Khadembashiri MM, Khadembashiri MA, Khafaie MA, Khajuria H, Khalafi M, Khalaji A, Khalid N, Khalil IA, Khamesipour F, Khan A, Khan G, Khan I, Khan IA, Khan M, Khan MAB, Khan T, Khan suheb MZ, Khanmohammadi S, Khatab K, Khatami F, Khavandegar A, Khayat Kashani HR, Kheirallah KA, Khidri FF, Khodadoust E, Khormali M, Khosrowjerdi M, Khubchandani J, Khusun H, Kifle ZD, Kim G, Kim J, Kimokoti RW, Kinzel KE, Kiross GT, Kisa A, Kisa S, Kiss JB, Kivimäki M, Klu D, Knudsen AKS, Kolahi AA, Kompani F, Koren G, Kosen S, Kostev K, Kotnis AL, Koul PA, Koulmane Laxminarayana SL, Koyanagi A, Kravchenko MA, Krishan K, Krishna H, Krishnamoorthy V, Krishnamoorthy Y, Krohn KJ, Kuate Defo B, Kubeisy CM, Kucuk Bicer B, Kuddus MA, Kuddus M, Kuitunen I, Kujan O, Kulimbet M, Kulkarni V, Kumar A, Kumar H, Kumar N, Kumar R, Kumar S, Kumari M, Kurmanova A, Kurmi OP, Kusnali A, Kusuma D, Kutluk T, Kuttikkattu A, Kyei EF, Kyriopoulos I, La Vecchia C, Ladan MA, Laflamme L, Lahariya C, Lahmar A, Lai DTC, Laksono T, Lal DK, Lalloo R, Lallukka T, Lám J, Lamnisos D, Lan T, Lanfranchi F, Langguth B, Lansingh VC, Laplante-Lévesque A, Larijani B, Larsson AO, Lasrado S, Latief K, Latif M, Latifinaibin K, Lauriola P, Le LKD, Le NHH, Le TTT, Le TDT, Lee M, Lee PH, Lee SW, Lee SW, Lee WC, Lee YH, Legesse SM, Leigh J, Lenzi J, Leong E, Lerango TL, Li MC, Li W, Li X, Li Y, Li Z, Libra M, Ligade VS, Likaka ATM, Lim LL, Lin RT, Lin S, Lioutas VA, Listl S, Liu J, Liu S, Liu X, Livingstone KM, Llanaj E, Lo CH, Loreche AM, Lorenzovici L, Lotfi M, Lotfizadeh M, Lozano R, Lubinda J, Lucchetti G, Lugo A, Lunevicius R, Ma J, Ma S, Ma ZF, Mabrok M, Machairas N, Machoy M, Madsen C, Magaña Gómez JA, Maghazachi AA, Maharaj SB, Maharjan P, Mahjoub S, Mahmoud MA, Mahmoudi E, Mahmoudi M, Makram OM, Malagón-Rojas JN, Malakan Rad E, Malekzadeh R, Malhotra AK, Malhotra K, Malik AA, Malik I, Malinga LA, Malta DC, Mamun AA, Manla Y, Mannan F, Mansoori Y, Mansour A, Mansouri V, Mansournia MA, Mantovani LG, Marasini BP, Marateb HR, Maravilla JC, Marconi AM, Mardi P, Marino M, Marjani A, Marrugo Arnedo CA, Martinez-Guerra BA, Martinez-Piedra R, Martins CA, Martins-Melo FR, Martorell M, Marx W, Maryam S, Marzo RR, Mate KKV, Matei CN, Mathioudakis AG, Maude RJ, Maugeri A, May EA, Mayeli M, Mazaheri M, Mazidi M, Mazzotti A, McAlinden C, McGrath JJ, McKee M, McKowen ALW, McLaughlin SA, McPhail MA, McPhail SM, Mechili EA, Mediratta RP, Meena JK, Mehari M, Mehlman ML, Mehra R, Mehrabani-Zeinabad K, Mehrabi Nasab E, Mehrotra R, Mekonnen MM, Mendoza W, Menezes RG, Mengesha EW, Mensah GA, Mensah LG, Mentis AFA, Meo SA, Meretoja A, Meretoja TJ, Mersha AM, Mesfin BA, Mestrovic T, Mhlanga A, Mhlanga L, Mi T, Micha G, Michalek IM, Miller TR, Mindlin SN, Minelli G, Minh LHN, Mini GK, Minja NW, Mirdamadi N, Mirghafourvand M, Mirica A, Mirinezhad SK, Mirmosayyeb O, Mirutse MK, Mirza-Aghazadeh-Attari M, Mirzaei M, Misgana T, Misra S, Mitchell PB, Mithra P, Mittal C, Mittal M, Moazen B, Mohamed AI, Mohamed J, Mohamed MFH, Mohamed NS, Mohammad-Alizadeh-Charandabi S, Mohammadi S, Mohammadian-Hafshejani A, Mohammad-pour S, Mohammadshahi M, Mohammed M, Mohammed S, Mohammed S, Mojiri-forushani H, Mokdad AH, Mokhtarzadehazar P, Momenzadeh K, Momtazmanesh S, Monasta L, Moni MA, Montazeri F, Moodi Ghalibaf A, Moradi M, Moradi Y, Moradi-Lakeh M, Moradinazar M, Moradpour F, Moraga P, Morawska L, Moreira RS, Morovatdar N, Morrison SD, Morze J, Mosaddeghi Heris R, Mosser JF, Mossialos E, Mostafavi H, Mostofinejad A, Mougin V, Mouodi S, Mousavi P, Mousavi SE, Mousavi Khaneghah A, Mpundu-Kaambwa C, Mrejen M, Mubarik S, Muccioli L, Mueller UO, Mughal F, Mukherjee S, Mukoro GD, Mulita A, Mulita F, Muniyandi M, Munjal K, Musaigwa F, Musallam KM, Mustafa G, Muthu S, Muthupandian S, Myung W, Nabhan AF, Nafukho FM, Nagarajan AJ, Naghavi M, Naghavi P, Naik GR, Naik G, Naimzada MD, Nair S, Nair TS, Najmuldeen HHR, Naldi L, Nangia V, Nargus S, Nascimento BR, Nascimento GG, Naser AY, Nasiri MJ, Natto ZS, Nauman J, Naveed M, Nayak BP, Nayak VC, Nayyar AK, Nazri-Panjaki A, Negash H, Negero AK, Negoi I, Negoi RI, Negru SM, Nejadghaderi SA, Nejjari C, Nematollahi MH, Nena E, Nepal S, Nesbit OD, Newton CRJ, Ngunjiri JW, Nguyen DH, Nguyen PT, Nguyen PT, Nguyen TT, Nguyen VT, Nigatu YT, Nikolouzakis TK, Nikoobar A, Nikpoor AR, Nizam MA, Nomura S, Noreen M, Noroozi N, Norouzian Baghani A, Norrving B, Noubiap JJ, Novotney A, Nri-Ezedi CA, Ntaios G, Ntsekhe M, Nuñez-Samudio V, Nurrika D, Oancea B, Obamiro KO, Odetokun IA, Ofakunrin AOD, Ogunsakin RE, Oguta JO, Oh IH, Okati-Aliabad H, Okeke SR, Okekunle AP, Okidi L, Okonji OC, Okwute PG, Olagunju AT, Olaiya MT, Olanipekun TO, Olatubi MI, Olivas-Martinez A, Oliveira GMM, Oliver S, Olorukooba AA, Olufadewa II, Olusanya BO, Olusanya JO, Oluwafemi YD, Oluwatunase GO, Omar HA, Omer GL, Ong S, Onwujekwe OE, Onyedibe KI, Opio JN, Ordak M, Orellana ER, Orisakwe OE, Orish VN, Orru H, Ortega-Altamirano DV, Ortiz A, Ortiz-Brizuela E, Ortiz-Prado E, Osuagwu UL, Otoiu A, Otstavnov N, Ouyahia A, Ouyang G, Owolabi MO, Oyeyemi IT, Oyeyemi OT, Ozten Y, P A MP, Padubidri JR, Pahlavikhah Varnosfaderani M, Pal PK, Palicz T, Palladino C, Palladino R, Palma-Alvarez RF, Pana A, Panahi P, Pandey A, Pandi-Perumal SR, Pando-Robles V, Pangaribuan HU, Panos GD, Pantazopoulos I, Papadopoulou P, Pardhan S, Parikh RR, Park S, Parthasarathi A, Pashaei A, Pasupula DK, Patel JR, Patel SK, Pathan AR, Patil A, Patil S, Patoulias D, Patthipati VS, Paudel U, Pawar S, Pazoki Toroudi H, Pease SA, Peden AE, Pedersini P, Peng M, Pensato U, Pepito VCF, Peprah EK, Pereira G, Pereira J, Pereira M, Peres MFP, Perianayagam A, Perico N, Petcu IR, Petermann-Rocha FE, Pezzani R, Pham HT, Phillips MR, Pierannunzio D, Pigeolet M, Pigott DM, Pilgrim T, Pinheiro M, Piradov MA, Plakkal N, Plotnikov E, Poddighe D, Pollner P, Poluru R, Pond CD, Postma MJ, Poudel GR, Poudel L, Pourali G, Pourtaheri N, Prada SI, Pradhan PMS, Prajapati VK, Prakash V, Prasad CP, Prasad M, Prashant A, Prates EJS, Purnobasuki H, Purohit BM, Puvvula J, Qaisar R, Qasim NH, Qattea I, Qian G, Quan NK, Radfar A, Radhakrishnan V, Raee P, Raeisi Shahraki H, Rafiei Alavi SN, Rafique I, Raggi A, Rahim F, Rahman MM, Rahman M, Rahman MA, Rahman T, Rahmani AM, Rahmani S, Rahnavard N, Rai P, Rajaa S, Rajabpour-Sanati A, Rajput P, Ram P, Ramadan H, Ramasamy SK, Ramazanu S, Rana J, Rana K, Ranabhat CL, Rancic N, Rani S, Ranjan S, Rao CR, Rao IR, Rao M, Rao SJ, Rasali DP, Rasella D, Rashedi S, Rashedi V, Rashid AM, Rasouli-Saravani A, Rastogi P, Rasul A, Ravangard R, Ravikumar N, Rawaf DL, Rawaf S, Rawassizadeh R, Razeghian-Jahromi I, Reddy MMRK, Redwan EMM, Rehman FU, Reiner Jr RC, Remuzzi G, Reshmi B, Resnikoff S, Reyes LF, Rezaee M, Rezaei N, Rezaei N, Rezaeian M, Riaz MA, Ribeiro AI, Ribeiro DC, Rickard J, Rios-Blancas MJ, Robinson-Oden HE, Rodrigues M, Rodriguez JAB, Roever L, Rohilla R, Rohloff P, Romadlon DS, Ronfani L, Roshandel G, Roshanzamir S, Rostamian M, Roy B, Roy P, Rubagotti E, Rumisha SF, Rwegerera GM, Rynkiewicz A, S M, S N C, S Sunnerhagen K, Saad AMA, Sabbatucci M, Saber K, Saber-Ayad MM, Sacco S, Saddik B, Saddler A, Sadee BA, Sadeghi E, Sadeghi M, Sadeghian S, Saeed U, Saeedi M, Safi S, Sagar R, Saghazadeh A, Saheb Sharif-Askari N, Sahoo SS, Sahraian MA, Sajedi SA, Sajid MR, Sakshaug JW, Salahi S, Salahi S, Salamati P, Salami AA, Salaroli LB, Saleh MA, Salehi S, Salem MR, Salem MZY, Salimi S, Samadi Kafil H, Samadzadeh S, Samara KA, Samargandy S, Samodra YL, Samuel VP, Samy AM, Sanabria J, Sanadgol N, Sanganyado E, Sanjeev RK, Sanmarchi F, Sanna F, Santri IN, Santric-Milicevic MM, Sarasmita MA, Saravanan A, Saravi B, Sarikhani Y, Sarkar C, Sarmiento-Suárez R, Sarode GS, Sarode SC, Sarveazad A, Sathian B, Sathish T, Sattin D, Saulam J, Sawyer SM, Saxena S, Saya GK, Sayadi Y, Sayeed A, Sayeed MA, Saylan M, Scarmeas N, Schaarschmidt BM, Schlee W, Schmidt MI, Schuermans A, Schwebel DC, Schwendicke F, Šekerija M, Selvaraj S, Semreen MH, Senapati S, Sengupta P, Senthilkumaran S, Sepanlou SG, Serban D, Sertsu A, Sethi Y, SeyedAlinaghi S, Seyedi SA, Shafaat A, Shafaat O, Shafie M, Shafiee A, Shah NS, Shah PA, Shahabi S, Shahbandi A, Shahid I, Shahid S, Shahid W, Shahwan MJ, Shaikh MA, Shakeri A, Shakil H, Sham S, Shamim MA, Shams-Beyranvand M, Shamshad H, Shamshirgaran MA, Shamsi MA, Shanawaz M, Shankar A, Sharfaei S, Sharifan A, Shariff M, Sharifi-Rad J, Sharma M, Sharma R, Sharma S, Sharma V, Shastry RP, Shavandi A, Shaw DH, Shayan AM, Shehabeldine AME, Sheikh A, Sheikhi RA, Shen J, Shenoy MM, Shetty BSK, Shetty RS, Shey RA, Shiani A, Shibuya K, Shiferaw D, Shigematsu M, Shin JI, Shin MJ, Shiri R, Shirkoohi R, Shittu A, Shiue I, Shivakumar KM, Shivarov V, Shool S, Shrestha S, Shuja KH, Shuval K, Si Y, Sibhat MM, Siddig EE, Sigfusdottir ID, Silva JP, Silva LMLR, Silva S, Simões JP, Simpson CR, Singal A, Singh A, Singh A, Singh A, Singh BB, Singh B, Singh M, Singh M, Singh NP, Singh P, Singh S, Siraj MS, Sitas F, Sivakumar S, Skryabin VY, Skryabina AA, Sleet DA, Slepak ELN, Sohrabi H, Soleimani H, Soliman SSM, Solmi M, Solomon Y, Song Y, Sorensen RJD, Soriano JB, Soyiri IN, Spartalis M, Sreeramareddy CT, Starnes JR, Starodubov VI, Starodubova AV, Stefan SC, Stein DJ, Steinbeis F, Steiropoulos P, Stockfelt L, Stokes MA, Stortecky S, Stranges S, Stroumpoulis K, Suleman M, Suliankatchi Abdulkader R, Sultana A, Sun J, Sunkersing D, Susanty S, Swain CK, Sykes BL, Szarpak L, Szeto MD, Szócska M, Tabaee Damavandi P, Tabatabaei Malazy O, Tabatabaeizadeh SA, Tabatabai S, Tabb KM, Tabish M, Taborda-Barata LM, Tabuchi T, Tadesse BT, Taheri A, Taheri Abkenar Y, Taheri Soodejani M, Taherkhani A, Taiba J, Tajbakhsh A, Talaat IM, Talukder A, Tamuzi JL, Tan KK, Tang H, Tang HK, Tat NY, Tat VY, Tavakoli Oliaee R, Tavangar SM, Taveira N, Tebeje TM, Tefera YM, Teimoori M, Temsah MH, Temsah RMH, Teramoto M, Tesfaye SH, Thangaraju P, Thankappan KR, Thapa R, Thapar R, Thomas N, Thrift AG, Thum CCC, Tian J, Tichopad A, Ticoalu JHV, Tiruye TY, Tohidast SA, Tonelli M, Touvier M, Tovani-Palone MR, Tram KH, Tran NM, Trico D, Trihandini I, Tromans SJ, Truong VT, Truyen TTTT, Tsermpini EE, Tumurkhuu M, Tung K, Tyrovolas S, Ubah CS, Udoakang AJ, Udoh A, Ulhaq I, Ullah S, Ullah S, Umair M, Umar TP, Umeokonkwo CD, Umesh A, Unim B, Unnikrishnan B, Upadhyay E, Urso D, Vacante M, Vahdani AM, Vaithinathan AG, Valadan Tahbaz S, Valizadeh R, Van den Eynde J, Varavikova E, Varga O, Varma SA, Vart P, Varthya SB, Vasankari TJ, Veerman LJ, Venketasubramanian N, Venugopal D, Verghese NA, Verma M, Verma P, Veroux M, Verras GI, Vervoort D, Vieira RJ, Villafañe JH, Villani L, Villanueva GI, Villeneuve PJ, Violante FS, Visontay R, Vlassov V, Vo B, Vollset SE, Volovat SR, Volovici V, Vongpradith A, Vos T, Vujcic IS, Vukovic R, Wado YD, Wafa HA, Waheed Y, Wamai RG, Wang C, Wang D, Wang F, Wang S, Wang S, Wang Y, Wang YP, Ward P, Watson S, Weaver MR, Weerakoon KG, Weiss DJ, Weldemariam AH, Wells KM, Wen YF, Werdecker A, Westerman R, Wickramasinghe DP, Wickramasinghe ND, Wijeratne T, Wilson S, Wojewodzic MW, Wool EE, Woolf AD, Wu D, Wulandari RD, Xiao H, Xu B, Xu X, Yadav L, Yaghoubi S, Yang L, Yano Y, Yao Y, Ye P, Yesera GE, Yesodharan R, Yesuf SA, Yiğit A, Yiğit V, Yip P, Yon DK, Yonemoto N, You Y, Younis MZ, Yu C, Zadey S, Zadnik V, Zafari N, Zahedi M, Zahid MN, Zahir M, Zakham F, Zaki N, Zakzuk J, Zamagni G, Zaman BA, Zaman SB, Zamora N, Zand R, Zandi M, Zandieh GGZ, Zanghì A, Zare I, Zastrozhin MS, Zeariya MGM, Zeng Y, Zhai C, Zhang C, Zhang H, Zhang H, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao Y, Zhao Y, Zheng P, Zhong C, Zhou J, Zhu B, Zhu Z, Ziaeefar P, Zielińska M, Zou Z, Zumla A, Zweck E, Zyoud SH, Lim SS, Murray CJL. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024:S0140-6736(24)00476-8. [PMID: 38484753 DOI: 10.1016/s0140-6736(24)00476-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/08/2023] [Accepted: 03/06/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020-21 COVID-19 pandemic period. METHODS 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5-65·1] decline), and increased during the COVID-19 pandemic period (2020-21; 5·1% [0·9-9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98-5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50-6·01) in 2019. An estimated 131 million (126-137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7-17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8-24·8), from 49·0 years (46·7-51·3) to 71·7 years (70·9-72·5). Global life expectancy at birth declined by 1·6 years (1·0-2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67-8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4-52·7]) and south Asia (26·3% [9·0-44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING Bill & Melinda Gates Foundation.
Collapse
|
4
|
Adikusuma W, Firdayani F, Irham LM, Darmawi D, Hamidy MY, Nopitasari BL, Soraya S, Azizah N. Integrated genomic network analysis revealed potential of a druggable target for hemorrhoid treatment. Saudi Pharm J 2023; 31:101831. [PMID: 37965490 PMCID: PMC10641558 DOI: 10.1016/j.jsps.2023.101831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 10/14/2023] [Indexed: 11/16/2023] Open
Abstract
Hemorrhoids are a prevalent medical condition that necessitates effective treatment options. The current options for treatment consist of oral medications, topical applications, or surgery, yet a scarcity of highly effective drugs still exists. Genetic markers provide promising avenues for investigating the treatment of hemorrhoids, as they may reveal intricate biological mechanisms and targeted drug therapies, ultimately enhancing more precise treatment tailored to the patient. This study aims to identify new drug candidates for treating hemorrhoids through a meticulous bioinformatics approach and integrated with genomic network analysis. After extracting 21 druggable target genes using DrugBank from 293 genes connected to hemorrhoids, 87 possible drugs were selected. Three of these drugs (ketamine, methylene blue, and fulvestrant) hold potential in addressing issues associated with hemorrhoids and have been supported by clinical or preclinical studies. Eighty-four compounds present new therapeutic possibilities for managing hemorrhoids. We highlight that our findings indicate that NOX1 and NOS3 genes are promising biomarkers, with NOS3 gaining significance owing to its robust systemic functional annotations. Sapropterin, an existing drug, is closely associated with NOS3, providing a clear target for biomarker-driven interventions. This study illustrates the potential of combining genomic network analysis with bioinformatics to repurpose drugs for treating hemorrhoids. Subsequent research will explore the mechanisms for utilizing NOS3 targeting in the treatment of hemorrhoids.
Collapse
Affiliation(s)
- Wirawan Adikusuma
- Departement of Pharmacy, University of Muhammadiyah Mataram, Mataram, Indonesia
- Research Center for Vaccine and Drugs, National Research and Innovation Agency (BRIN), South Tangerang, Indonesia
| | - Firdayani Firdayani
- Research Center for Vaccine and Drugs, National Research and Innovation Agency (BRIN), South Tangerang, Indonesia
| | | | - Darmawi Darmawi
- Department of Histology, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia
- Graduate School in Biomedical Sciences, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia
| | - Muhammad Yulis Hamidy
- Department of Pharmacology, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia
| | | | - Soraya Soraya
- Master Program in Biomedical Sciences, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia
| | - Nurul Azizah
- Master Program in Biomedical Sciences, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia
| |
Collapse
|
5
|
Ma’ruf M, Irham LM, Adikusuma W, Sarasmita MA, Khairi S, Purwanto BD, Chong R, Mazaya M, Siswanto LMH. A genomic and bioinformatic-based approach to identify genetic variants for liver cancer across multiple continents. Genomics Inform 2023; 21:e48. [PMID: 38224715 PMCID: PMC10788354 DOI: 10.5808/gi.23067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 01/17/2024] Open
Abstract
Liver cancer is the fourth leading cause of death worldwide. Well-known risk factors include hepatitis B virus and hepatitis C virus, along with exposure to aflatoxins, excessive alcohol consumption, obesity, and type 2 diabetes. Genomic variants play a crucial role in mediating the associations between these risk factors and liver cancer. However, the specific variants involved in this process remain under-explored. This study utilized a bioinformatics approach to identify genetic variants associated with liver cancer from various continents. Single-nucleotide polymorphisms associated with liver cancer were retrieved from the genome-wide association studies catalog. Prioritization was then performed using functional annotation with HaploReg v4.1 and the Ensembl database. The prevalence and allele frequencies of each variant were evaluated using Pearson correlation coefficients. Two variants, rs2294915 and rs2896019, encoded by the PNPLA3 gene, were found to be highly expressed in the liver tissue, as well as in the skin, cell-cultured fibroblasts, and adipose-subcutaneous tissue, all of which contribute to the risk of liver cancer. We further found that these two SNPs (rs2294915 and rs2896019) were positively correlated with the prevalence rate. Positive associations with the prevalence rate were more frequent in East Asian and African populations. We highlight the utility of this population-specific PNPLA3 genetic variant for genetic association studies and for the early prognosis and treatment of liver cancer. This study highlights the potential of integrating genomic databases with bioinformatic analysis to identify genetic variations involved in the pathogenesis of liver cancer. The genetic variants investigated in this study are likely to predispose to liver cancer and could affect its progression and aggressiveness. We recommend future research prioritizing the validation of these variations in clinical settings.
Collapse
Affiliation(s)
- Muhammad Ma’ruf
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55164, Indonesia
| | | | - Wirawan Adikusuma
- Departement of Pharmacy, University of Muhammadiyah Mataram, Mataram 83127, Indonesia
| | - Made Ary Sarasmita
- Department of Clinical Pharmacy, College of Pharmacy, Taipei Medical University, Taipei 110, Taiwan
- Pharmacy Study Program, Faculty of Science and Mathematics, Udayana University, Bali, Indonesia
| | - Sabiah Khairi
- School of Nursing, College of Nursing, Taipei Medical University, Taipei 11031, Taiwan
| | - Barkah Djaka Purwanto
- Faculty of Medicine, Universitas Ahmad Dahlan, Yogyakarta 55191, Indonesia
- PKU Muhammadiyah Bantul Hospital, Bantul, Yogyakarta 55711, Indonesia
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Maulida Mazaya
- Research Center for Computing, Research Organization for Electronics and Informatics, National Research and Innovation Agency (BRIN), Cibinong Science Center, Cibinong 16911, Indonesia
| | | |
Collapse
|
6
|
Satria RD, Irham LM, Adikusuma W, Puspitaningrum AN, Afief AR, Khair RE, Septama AW. Identification of druggable genes for multiple myeloma based on genomic information. Genomics Inform 2023; 21:e31. [PMID: 37813627 PMCID: PMC10584652 DOI: 10.5808/gi.23011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 05/08/2023] [Accepted: 08/07/2023] [Indexed: 10/11/2023] Open
Abstract
Multiple myeloma (MM) is a hematological malignancy. It is widely believed that genetic factors play a significant role in the development of MM, as investigated in numerous studies. However, the application of genomic information for clinical purposes, including diagnostic and prognostic biomarkers, remains largely confined to research. In this study, we utilized genetic information from the Genomic-Driven Clinical Implementation for Multiple Myeloma database, which is dedicated to clinical trial studies on MM. This genetic information was sourced from the genome-wide association studies catalog database. We prioritized genes with the potential to cause MM based on established annotations, as well as biological risk genes for MM, as potential drug target candidates. The DrugBank database was employed to identify drug candidates targeting these genes. Our research led to the discovery of 14 MM biological risk genes and the identification of 10 drugs that target three of these genes. Notably, only one of these 10 drugs, panobinostat, has been approved for use in MM. The two most promising genes, calcium signal-modulating cyclophilin ligand (CAMLG) and histone deacetylase 2 (HDAC2), were targeted by four drugs (cyclosporine, belinostat, vorinostat, and romidepsin), all of which have clinical evidence supporting their use in the treatment of MM. Interestingly, five of the 10 drugs have been approved for other indications than MM, but they may also be effective in treating MM. Therefore, this study aimed to clarify the genomic variants involved in the pathogenesis of MM and highlight the potential benefits of these genomic variants in drug discovery.
Collapse
Affiliation(s)
- Rahmat Dani Satria
- Department of Clinical Pathology and Laboratory Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
- Clinical Laboratory Installation, Dr. Sardjito Central General Hospital, Yogyakarta 55281, Indonesia
| | - Lalu Muhammad Irham
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55164, Indonesia
- Research Centre for Pharmaceutical Ingredients and Traditional Medicine, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia
| | - Wirawan Adikusuma
- Department of Pharmacy, University of Muhammadiyah Mataram, Mataram 83127, Indonesia
- Research Center for Vaccine and Drugs, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia
| | | | - Arief Rahman Afief
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55164, Indonesia
| | - Riat El Khair
- Department of Clinical Pathology and Laboratory Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
- Clinical Laboratory Installation, Dr. Sardjito Central General Hospital, Yogyakarta 55281, Indonesia
| | - Abdi Wira Septama
- Research Center for Vaccine and Drugs, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia
| |
Collapse
|
7
|
Irham LM, Adikusuma W, La’ah AS, Chong R, Septama AW, Angelina M. Leveraging Genomic and Bioinformatic Analysis to Enhance Drug Repositioning for Dermatomyositis. Bioengineering (Basel) 2023; 10:890. [PMID: 37627776 PMCID: PMC10451728 DOI: 10.3390/bioengineering10080890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/13/2023] [Accepted: 04/19/2023] [Indexed: 08/27/2023] Open
Abstract
Dermatomyositis (DM) is an autoimmune disease that is classified as a type of idiopathic inflammatory myopathy, which affects human skin and muscles. The most common clinical symptoms of DM are muscle weakness, rash, and scaly skin. There is currently no cure for DM. Genetic factors are known to play a pivotal role in DM progression, but few have utilized this information geared toward drug discovery for the disease. Here, we exploited genomic variation associated with DM and integrated this with genomic and bioinformatic analyses to discover new drug candidates. We first integrated genome-wide association study (GWAS) and phenome-wide association study (PheWAS) catalogs to identify disease-associated genomic variants. Biological risk genes for DM were prioritized using strict functional annotations, further identifying candidate drug targets based on druggable genes from databases. Overall, we analyzed 1239 variants associated with DM and obtained 43 drugs that overlapped with 13 target genes (JAK2, FCGR3B, CD4, CD3D, LCK, CD2, CD3E, FCGR3A, CD3G, IFNAR1, CD247, JAK1, IFNAR2). Six drugs clinically investigated for DM, as well as eight drugs under pre-clinical investigation, are candidate drugs that could be repositioned for DM. Further studies are necessary to validate potential biomarkers for novel DM therapeutics from our findings.
Collapse
Affiliation(s)
- Lalu Muhammad Irham
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55164, Indonesia
- Research Centre for Pharmaceutical Ingredients and Traditional Medicine, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia
| | - Wirawan Adikusuma
- Department of Pharmacy, University of Muhammadiyah Mataram, Mataram 83127, Indonesia
- Research Center for Vaccine and Drugs, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia
| | - Anita Silas La’ah
- Taiwan International Graduate Program in Molecular Medicine, National Yang Ming Chiao Tung University and Academia Sinica, Taipei 112304, Taiwan
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA
| | - Abdi Wira Septama
- Research Centre for Pharmaceutical Ingredients and Traditional Medicine, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia
| | - Marissa Angelina
- Research Centre for Pharmaceutical Ingredients and Traditional Medicine, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia
| |
Collapse
|
8
|
Adikusuma W, Zakaria ZA, Irham LM, Nopitasari BL, Pradiningsih A, Firdayani F, Septama AW, Chong R. Transcriptomics-driven drug repositioning for the treatment of diabetic foot ulcer. Sci Rep 2023; 13:10032. [PMID: 37340026 DOI: 10.1038/s41598-023-37120-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 06/15/2023] [Indexed: 06/22/2023] Open
Abstract
Diabetic foot ulcers (DFUs) are a common complication of diabetes and can lead to severe disability and even amputation. Despite advances in treatment, there is currently no cure for DFUs and available drugs for treatment are limited. This study aimed to identify new candidate drugs and repurpose existing drugs to treat DFUs based on transcriptomics analysis. A total of 31 differentially expressed genes (DEGs) were identified and used to prioritize the biological risk genes for DFUs. Further investigation using the database DGIdb revealed 12 druggable target genes among 50 biological DFU risk genes, corresponding to 31 drugs. Interestingly, we highlighted that two drugs (urokinase and lidocaine) are under clinical investigation for DFU and 29 drugs are potential candidates to be repurposed for DFU therapy. The top 5 potential biomarkers for DFU from our findings are IL6ST, CXCL9, IL1R1, CXCR2, and IL10. This study highlights IL1R1 as a highly promising biomarker for DFU due to its high systemic score in functional annotations, that can be targeted with an existing drug, Anakinra. Our study proposed that the integration of transcriptomic and bioinformatic-based approaches has the potential to drive drug repurposing for DFUs. Further research will further examine the mechanisms by which targeting IL1R1 can be used to treat DFU.
Collapse
Affiliation(s)
- Wirawan Adikusuma
- Borneo Research on Algesia, Inflammation, and Neurodegeneration (BRAIN) Group, Department of Biomedical Sciences, Faculty of Medicines and Health Sciences, University Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
- Departement of Pharmacy, University of Muhammadiyah Mataram, Mataram, Indonesia.
- Research Center for Vaccine and Drugs, National Research and Innovation Agency (BRIN), South Tangerang, Indonesia.
| | - Zainul Amiruddin Zakaria
- Borneo Research on Algesia, Inflammation, and Neurodegeneration (BRAIN) Group, Department of Biomedical Sciences, Faculty of Medicines and Health Sciences, University Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
| | - Lalu Muhammad Irham
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
- Research Center for Pharmaceutical Ingredients and Traditional Medicine, National Research and Innovation Agency (BRIN), South Tangerang, Indonesia
| | | | - Anna Pradiningsih
- Departement of Pharmacy, University of Muhammadiyah Mataram, Mataram, Indonesia
| | - Firdayani Firdayani
- Research Center for Vaccine and Drugs, National Research and Innovation Agency (BRIN), South Tangerang, Indonesia
| | - Abdi Wira Septama
- Research Center for Pharmaceutical Ingredients and Traditional Medicine, National Research and Innovation Agency (BRIN), South Tangerang, Indonesia
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, USA
| |
Collapse
|
9
|
Ma’ruf M, Fadli JC, Mahendra MR, Irham LM, Sulistyani N, Adikusuma W, Chong R, Septama AW. A bioinformatic approach to identify pathogenic variants for Stevens-Johnson syndrome. Genomics Inform 2023; 21:e26. [PMID: 37704211 PMCID: PMC10326529 DOI: 10.5808/gi.23010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/09/2023] [Accepted: 04/12/2023] [Indexed: 07/08/2023] Open
Abstract
Stevens-Johnson syndrome (SJS) produces a severe hypersensitivity reaction caused by Herpes simplex virus or mycoplasma infection, vaccination, systemic disease, or other agents. Several studies have investigated the genetic susceptibility involved in SJS. To provide further genetic insights into the pathogenesis of SJS, this study prioritized high-impact, SJS-associated pathogenic variants through integrating bioinformatic and population genetic data. First, we identified SJS-associated single nucleotide polymorphisms from the genome-wide association studies catalog, followed by genome annotation with HaploReg and variant validation with Ensembl. Subsequently, expression quantitative trait locus (eQTL) from GTEx identified human genetic variants with differential gene expression across human tissues. Our results indicate that two variants, namely rs2074494 and rs5010528, which are encoded by the HLA-C (human leukocyte antigen C) gene, were found to be differentially expressed in skin. The allele frequencies for rs2074494 and rs5010528 also appear to significantly differ across continents. We highlight the utility of these population-specific HLA-C genetic variants for genetic association studies, and aid in early prognosis and disease treatment of SJS.
Collapse
Affiliation(s)
- Muhammad Ma’ruf
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55164, Indonesia
| | | | | | - Lalu Muhammad Irham
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55164, Indonesia
- Center for Vaccine and Drugs, Research Organization for Health, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia
| | - Nanik Sulistyani
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55164, Indonesia
| | - Wirawan Adikusuma
- Departement of Pharmacy, University of Muhammadiyah Mataram, Mataram 83127, Indonesia
- Center for Vaccine and Drugs, Research Organization for Health, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, CA, USA
| | - Abdi Wira Septama
- Departement of Pharmacy, University of Muhammadiyah Mataram, Mataram 83127, Indonesia
| |
Collapse
|
10
|
Ayu Eka Pitaloka D, Izzati A, Rafa Amirah S, Abdan Syakuran L, Muhammad Irham L, Darumas Putri A, Adikusuma W. Bioinformatics Analysis to Uncover the Potential Drug Targets Responsible for Mycobacterium tuberculosis Peptidoglycan and Lysine Biosynthesis. Bioinform Biol Insights 2023; 17:11779322231171774. [PMID: 37187890 PMCID: PMC10176782 DOI: 10.1177/11779322231171774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 04/07/2023] [Indexed: 05/17/2023] Open
Abstract
Drug-resistant tuberculosis (TB), which results mainly from the selection of naturally resistant strains of Mycobacterium tuberculosis (MTB) due to mismanaged treatment, poses a severe challenge to the global control of TB. Therefore, screening novel and unique drug targets against this pathogen is urgently needed. The metabolic pathways of Homo sapiens and MTB were compared using the Kyoto Encyclopedia of Genes and Genomes tool, and further, the proteins that are involved in the metabolic pathways of MTB were subtracted and proceeded to protein-protein interaction network analysis, subcellular localization, drug ability testing, and gene ontology. The study aims to identify enzymes for the unique pathways for further screening to determine the feasibility of the therapeutic targets. The qualitative characteristics of 28 proteins identified as drug target candidates were studied. The results showed that 12 were cytoplasmic, 2 were extracellular, 12 were transmembrane, and 3 were unknown. Furthermore, druggability analysis revealed 14 druggable proteins, of which 12 were novel and responsible for MTB peptidoglycan and lysine biosynthesis. The novel targets obtained in this study are used to develop antimicrobial treatments against pathogenic bacteria. Future studies should further shed light on the clinical implementation to identify antimicrobial therapies against MTB.
Collapse
Affiliation(s)
- Dian Ayu Eka Pitaloka
- Department of Pharmacology and Clinical
Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, Indonesia
- Center for Translational Biomarker
Research, Universitas Padjadjaran, Sumedang, Indonesia
| | - Afifah Izzati
- Department of Pharmacology and Clinical
Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, Indonesia
| | - Siti Rafa Amirah
- Department of Pharmacology and Clinical
Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, Indonesia
| | - Luqman Abdan Syakuran
- Genetics and Molecular Laboratory,
Faculty of Biology, Jenderal Soedirman University, Purwokerto, Indonesia
| | - Lalu Muhammad Irham
- Faculty of Pharmacy, Universitas Ahmad
Dahlan, Yogyakarta, Indonesia
- Research Center for Pharmaceutical
Ingrediensts and Traditional Medicine, National Research and Inovation Agency
(BRIN), South Tangerang, Indonesia
| | | | - Wirawan Adikusuma
- Department of Pharmacy, Faculty of
Health Science, Universitas Muhammadiyah Mataram, Mataram, Indonesia
- Research Center for Vaccine and Drugs,
National Research and Inovation Agency (BRIN), South Tangerang, Indonesia
| |
Collapse
|
11
|
Irham LM, Adikusuma W, Lolita L, Puspitaningrum AN, Afief AR, Sarasmita MA, Dania H, Khairi S, Djalilah GN, Purwanto BD, Chong R. Investigation of susceptibility genes for chickenpox disease across multiple continents. Biochem Biophys Rep 2023; 33:101419. [PMID: 36620086 PMCID: PMC9816662 DOI: 10.1016/j.bbrep.2022.101419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 12/01/2022] [Accepted: 12/23/2022] [Indexed: 01/01/2023] Open
Abstract
Chickenpox (varicella) is caused by infection with the varicella-zoster virus (VZV), a neurotropic alpha herpes virus with a double-stranded DNA genome. Chickenpox can cause life-threatening complications, including subsequent bacterial infections, central nervous system symptoms, and even death without any risk factors. Few studies have been reported to investigate genetic susceptibility implicated in chickenpox. Herein, our study identified global genetic variants that potentially contributed to chickenpox susceptibility by utilizing the established bioinformatic-based approach. We integrated several databases, such as genome-wide association studies (GWAS) catalog, GTEx portal, HaploReg version 4.1, and Ensembl databases analyses to investigate susceptibility genes associated with chickenpox. Notably, increased expression of HLA-S, HCG4P5, and ABHD16A genes underlie enhanced chickenpox susceptibility in the European, American, and African populations. As compared to the Asian population, Europeans, Americans, and Africans have higher allele frequencies of the extant variants rs9266089, rs10947050, and rs79501286 from the susceptibility genes. Our study suggested that these susceptibility genes and associated genetic variants might play a critical role in chickenpox progression based on host genetics with clinical implications.
Collapse
Affiliation(s)
| | - Wirawan Adikusuma
- Department of Pharmacy, University of Muhammadiyah Mataram, Mataram, Indonesia
| | - Lolita Lolita
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
| | | | | | - Made Ary Sarasmita
- Pharmacy Study Program, Faculty of Science and Mathematics, Udayana University, Bali, Indonesia
| | - Haafizah Dania
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
| | - Sabiah Khairi
- School of Nursing, College of Nursing, Taipei Medical University, Taipei, 11031, Taiwan
| | | | - Barkah Djaka Purwanto
- Faculty of Medicine, University of Ahmad Dahlan, Yogyakarta, 55191, Indonesia
- PKU Muhammadiyah Bantul Hospital, Bantul, Yogyakarta, 55711, Indonesia
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, USA
| |
Collapse
|
12
|
Mugiyanto E, Adikusuma W, Irham LM, Huang WC, Chang WC, Kuo CN. Integrated genomic analysis to identify druggable targets for pancreatic cancer. Front Oncol 2022; 12:989077. [PMID: 36531045 PMCID: PMC9752886 DOI: 10.3389/fonc.2022.989077] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/19/2022] [Indexed: 03/31/2024] Open
Abstract
According to the National Comprehensive Cancer Network and the American Society of Clinical Oncology, the standard treatment for pancreatic cancer (PC) is gemcitabine and fluorouracil. Other chemotherapeutic agents have been widely combined. However, drug resistance remains a huge challenge, leading to the ineffectiveness of cancer therapy. Therefore, we are trying to discover new treatments for PC by utilizing genomic information to identify PC-associated genes as well as drug target genes for drug repurposing. Genomic information from a public database, the cBio Cancer Genomics Portal, was employed to retrieve the somatic mutation genes of PC. Five functional annotations were applied to prioritize the PC risk genes: Kyoto Encyclopedia of Genes and Genomes; biological process; knockout mouse; Gene List Automatically Derived For You; and Gene Expression Omnibus Dataset. DrugBank database was utilized to extract PC drug targets. To narrow down the most promising drugs for PC, CMap Touchstone analysis was applied. Finally, ClinicalTrials.gov and a literature review were used to screen the potential drugs under clinical and preclinical investigation. Here, we extracted 895 PC-associated genes according to the cBioPortal database and prioritized them by using five functional annotations; 318 genes were assigned as biological PC risk genes. Further, 216 genes were druggable according to the DrugBank database. CMap Touchstone analysis indicated 13 candidate drugs for PC. Among those 13 drugs, 8 drugs are in the clinical trials, 2 drugs were supported by the preclinical studies, and 3 drugs are with no evidence status for PC. Importantly, we found that midostaurin (targeted PRKA) and fulvestrant (targeted ESR1) are promising candidate drugs for PC treatment based on the genomic-driven drug repurposing pipelines. In short, integrated analysis using a genomic information database demonstrated the viability for drug repurposing. We proposed two drugs (midostaurin and fulvestrant) as promising drugs for PC.
Collapse
Affiliation(s)
- Eko Mugiyanto
- PhD Program in Clinical Drug Development of Herbal Medicine, College of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Pharmacy, Faculty of Health Science, University of Muhammadiyah Pekajangan Pekalongan, Pekalongan, Indonesia
| | - Wirawan Adikusuma
- Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Pharmacy, Faculty of Health Science, University of Muhammadiyah Mataram, Mataram, Indonesia
| | | | - Wan-Chen Huang
- Institute of Cellular and Organismic Biology, Academia Sinica, Taipei, Taiwan
| | - Wei-Chiao Chang
- PhD Program in Clinical Drug Development of Herbal Medicine, College of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Pharmacy, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
- Integrative Research Center for Critical Care, Department of Pharmacy, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Chun-Nan Kuo
- Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Pharmacy, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| |
Collapse
|
13
|
Afief AR, Irham LM, Adikusuma W, Perwitasari DA, Brahmadhi A, Chong R. Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis. Biochem Biophys Rep 2022; 32:101337. [PMID: 36105612 PMCID: PMC9464879 DOI: 10.1016/j.bbrep.2022.101337] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 08/25/2022] [Accepted: 08/25/2022] [Indexed: 01/04/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic autoimmune disease in the central nervous system (CNS) marked by inflammation, demyelination, and axonal loss. Currently available MS medication is limited, thereby calling for a strategy to accelerate new drug discovery. One of the strategies to discover new drugs is to utilize old drugs for new indications, an approach known as drug repurposing. Herein, we first identified 421 MS-associated SNPs from the Genome-Wide Association Study (GWAS) catalog (p-value < 5 × 10-8), and a total of 427 risk genes associated with MS using HaploReg version 4.1 under the criterion r 2 > 0.8. MS risk genes were then prioritized using bioinformatics analysis to identify biological MS risk genes. The prioritization was performed based on six defined categories of functional annotations, namely missense mutation, cis-expression quantitative trait locus (cis-eQTL), molecular pathway analysis, protein-protein interaction (PPI), genes overlap with knockout mouse phenotype, and primary immunodeficiency (PID). A total of 144 biological MS risk genes were found and mapped into 194 genes within an expanded PPI network. According to the DrugBank and the Therapeutic Target Database, 27 genes within the list targeted by 68 new candidate drugs were identified. Importantly, the power of our approach is confirmed with the identification of a known approved drug (dimethyl fumarate) for MS. Based on additional data from ClinicalTrials.gov, eight drugs targeting eight distinct genes are prioritized with clinical evidence for MS disease treatment. Notably, CD80 and CD86 pathways are promising targets for MS drug repurposing. Using in silico drug repurposing, we identified belatacept as a promising MS drug candidate. Overall, this study emphasized the integration of functional genomic variants and bioinformatic-based approach that reveal important biological insights for MS and drive drug repurposing efforts for the treatment of this devastating disease.
Collapse
Key Words
- ARE, Antioxidant Response Element
- ASN, Asian
- Autoimmune disease
- Bioinformatics
- CNS, Central Nervous System
- Drug repurposing
- FDA, Food and Drug Administration
- FDR, False Discovery Rate
- GO, Gene Ontology
- GWAS, Genome-Wide Association Study
- Genomic variants
- HLA, Human Leukocyte Antigen
- KEGG, Kyoto Encyclopedia of Genes and Genomes
- MP, Mammalian Phenotype
- MS, Multiple Sclerosis
- Multiple sclerosis
- PID, Primary Immuno-deficiency
- PPI, Protein-Protein Interaction
- SNP, Single Nucleotide Polymorphism
- cis-eQTL, cis-expression Quantitative Trait Locus
Collapse
Affiliation(s)
| | | | - Wirawan Adikusuma
- Department of Pharmacy, University of Muhammadiyah Mataram, Mataram, Indonesia
| | | | - Ageng Brahmadhi
- Faculty of Medicine, Universitas Muhammadiyah Purwokerto, Purwokerto, Central Java, Indonesia
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, USA
| |
Collapse
|
14
|
Santri IN, Irham LM, Djalilah GN, Perwitasari DA, Wardani Y, Phiri YVA, Adikusuma W. Identification of Hub Genes and Potential Biomarkers for Childhood Asthma by Utilizing an Established Bioinformatic Analysis Approach. Biomedicines 2022; 10:biomedicines10092311. [PMID: 36140412 PMCID: PMC9496621 DOI: 10.3390/biomedicines10092311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 09/08/2022] [Accepted: 09/13/2022] [Indexed: 11/23/2022] Open
Abstract
Childhood asthma represents a heterogeneous disease resulting from the interaction between genetic factors and environmental exposures. Currently, finding reliable biomarkers is necessary for the clinical management of childhood asthma. However, only a few biomarkers are being used in clinical practice in the pediatric population. In the long run, new biomarkers for asthma in children are required and would help direct therapy approaches. This study aims to identify potential childhood asthma biomarkers using a genetic-driven biomarkers approach. Herein, childhood asthma-associated Single Nucleotide Polymorphisms (SNPs) were utilized from the GWAS database to drive and facilitate the biomarker of childhood asthma. We uncovered 466 childhood asthma-associated loci by extending to proximal SNPs based on r2 > 0.8 in Asian populations and utilizing HaploReg version 4.1 to determine 393 childhood asthma risk genes. Next, the functional roles of these genes were subsequently investigated using Gene Ontology (GO) term enrichment analysis, a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and a protein−protein interaction (PPI) network. MCODE and CytoHubba are two Cytoscape plugins utilized to find biomarker genes from functional networks created using childhood asthma risk genes. Intriguingly, 10 hub genes (IL6, IL4, IL2, IL13, PTPRC, IL5, IL33, TBX21, IL2RA, and STAT6) were successfully identified and may have been identified to play a potential role in the pathogenesis of childhood asthma. Among 10 hub genes, we strongly suggest IL6 and IL4 as prospective childhood asthma biomarkers since both of these biomarkers achieved a high systemic score in Cytohubba’s MCC algorithm. In summary, this study offers a valuable genetic-driven biomarker approach to facilitate the potential biomarkers for asthma in children.
Collapse
Affiliation(s)
| | | | | | | | - Yuniar Wardani
- Faculty of Public Health, Universitas Ahmad Dahlan, Yogyakarta 55164, Indonesia
| | - Yohane Vincent Abero Phiri
- School of Public Health, College of Public Health, Taipei Medical University, Taipei 11031, Taiwan
- Institute for Health Research and Communication (IHRC), Lilongwe P.O. Box 1958, Malawi
| | - Wirawan Adikusuma
- Departement of Pharmacy, University of Muhammadiyah Mataram, Mataram 83127, Indonesia
- Correspondence: (W.A.)
| |
Collapse
|
15
|
Irham LM, Adikusuma W, Perwitasari DA, Dania H, Maliza R, Faridah IN, Santri IN, Phiri YVA, Chong R. The use of genomic variants to drive drug repurposing for chronic hepatitis B. Biochem Biophys Rep 2022; 31:101307. [PMID: 35832745 PMCID: PMC9271961 DOI: 10.1016/j.bbrep.2022.101307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 06/25/2022] [Accepted: 06/28/2022] [Indexed: 10/27/2022] Open
Abstract
Background One of the main challenges in personalized medicine is to establish and apply a large number of variants from genomic databases into clinical diagnostics and further facilitate genome-driven drug repurposing. By utilizing biological chronic hepatitis B infection (CHB) risk genes, our study proposed a systematic approach to use genomic variants to drive drug repurposing for CHB. Method The genomic variants were retrieved from the Genome-Wide Association Study (GWAS) and Phenome-Wide Association Study (PheWAS) databases. Then, the biological CHB risk genes crucial for CHB progression were prioritized based on the scoring system devised with five strict functional annotation criteria. A score of ≥ 2 were categorized as the biological CHB risk genes and further shed light on drug target genes for CHB treatments. Overlapping druggable targets were identified using two drug databases (DrugBank and Drug-Gene Interaction Database (DGIdb)). Results A total of 44 biological CHB risk genes were screened based on the scoring system from five functional annotation criteria. Interestingly, we found 6 druggable targets that overlapped with 18 drugs with status of undergoing clinical trials for CHB, and 9 druggable targets that overlapped with 20 drugs undergoing preclinical investigations for CHB. Eight druggable targets were identified, overlapping with 25 drugs that can potentially be repurposed for CHB. Notably, CD40 and HLA-DPB1 were identified as promising targets for CHB drug repurposing based on the target scores. Conclusion Through the integration of genomic variants and a bioinformatic approach, our findings suggested the plausibility of CHB genomic variant-driven drug repurposing for CHB.
Collapse
Affiliation(s)
| | - Wirawan Adikusuma
- Departement of Pharmacy, University of Muhammadiyah Mataram, Mataram, Indonesia
| | | | - Haafizah Dania
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
| | - Rita Maliza
- Biology Department, Faculty of Mathematics and Natural Sciences, Andalas University, Padang, West Sumatra, Indonesia
| | | | | | - Yohane Vincent Abero Phiri
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan
- Institute for Health Research and Communication (IHRC), P.O Box 1958, Lilongwe, Malawi
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, USA
| |
Collapse
|
16
|
Adikusuma W, Chou WH, Lin MR, Ting J, Irham LM, Perwitasari DA, Chang WP, Chang WC. Identification of Druggable Genes for Asthma by Integrated Genomic Network Analysis. Biomedicines 2022; 10:biomedicines10010113. [PMID: 35052792 PMCID: PMC8773254 DOI: 10.3390/biomedicines10010113] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 12/22/2021] [Accepted: 12/24/2021] [Indexed: 02/01/2023] Open
Abstract
Asthma is a common and heterogeneous disease characterized by chronic airway inflammation. Currently, the two main types of asthma medicines are inhaled corticosteroids and long-acting β2-adrenoceptor agonists (LABAs). In addition, biological drugs provide another therapeutic option, especially for patients with severe asthma. However, these drugs were less effective in preventing severe asthma exacerbation, and other drug options are still limited. Herein, we extracted asthma-associated single nucleotide polymorphisms (SNPs) from the genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS) catalog and prioritized candidate genes through five functional annotations. Genes enriched in more than two categories were defined as “biological asthma risk genes.” Then, DrugBank was used to match target genes with FDA-approved medications and identify candidate drugs for asthma. We discovered 139 biological asthma risk genes and identified 64 drugs targeting 22 of these genes. Seven of them were approved for asthma, including reslizumab, mepolizumab, theophylline, dyphylline, aminophylline, oxtriphylline, and enprofylline. We also found 17 drugs with clinical or preclinical evidence in treating asthma. In addition, eleven of the 40 candidate drugs were further identified as promising asthma therapy. Noteworthy, IL6R is considered a target for asthma drug repurposing based on its high target scores. Through in silico drug repurposing approach, we identified sarilumab and satralizumab as the most promising drug for asthma treatment.
Collapse
Affiliation(s)
- Wirawan Adikusuma
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan; (W.A.); (W.-H.C.); (M.-R.L.); (J.T.)
- Department of Pharmacy, Faculty of Health Science, University of Muhammadiyah Mataram, Mataram 83127, Indonesia
| | - Wan-Hsuan Chou
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan; (W.A.); (W.-H.C.); (M.-R.L.); (J.T.)
| | - Min-Rou Lin
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan; (W.A.); (W.-H.C.); (M.-R.L.); (J.T.)
| | - Jafit Ting
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan; (W.A.); (W.-H.C.); (M.-R.L.); (J.T.)
| | - Lalu Muhammad Irham
- Faculty of Pharmacy, University of Ahmad Dahlan, Yogyakarta 55164, Indonesia; (L.M.I.); (D.A.P.)
| | - Dyah Aryani Perwitasari
- Faculty of Pharmacy, University of Ahmad Dahlan, Yogyakarta 55164, Indonesia; (L.M.I.); (D.A.P.)
| | - Wei-Pin Chang
- School of Health Care Administration, College of Management, Taipei Medical University, Taipei 11031, Taiwan
- Correspondence: (W.-P.C.); (W.-C.C.)
| | - Wei-Chiao Chang
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan; (W.A.); (W.-H.C.); (M.-R.L.); (J.T.)
- TMU Research Center of Cancer Translational Medicine, Taipei 11031, Taiwan
- Department of Pharmacy, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
- Integrative Research Center for Critical Care, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
- Department of Pharmacology, National Defense Medical Center, Taipei 11490, Taiwan
- Correspondence: (W.-P.C.); (W.-C.C.)
| |
Collapse
|
17
|
Adikusuma W, Irham LM, Chou WH, Wong HSC, Mugiyanto E, Ting J, Perwitasari DA, Chang WP, Chang WC. Drug Repurposing for Atopic Dermatitis by Integration of Gene Networking and Genomic Information. Front Immunol 2021; 12:724277. [PMID: 34721386 PMCID: PMC8548825 DOI: 10.3389/fimmu.2021.724277] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 09/15/2021] [Indexed: 12/02/2022] Open
Abstract
Atopic Dermatitis (AD) is a chronic and relapsing skin disease. The medications for treating AD are still limited, most of them are topical corticosteroid creams or antibiotics. The current study attempted to discover potential AD treatments by integrating a gene network and genomic analytic approaches. Herein, the Single Nucleotide Polymorphism (SNPs) associated with AD were extracted from the GWAS catalog. We identified 70 AD-associated loci, and then 94 AD risk genes were found by extending to proximal SNPs based on r2 > 0.8 in Asian populations using HaploReg v4.1. Next, we prioritized the AD risk genes using in silico pipelines of bioinformatic analysis based on six functional annotations to identify biological AD risk genes. Finally, we expanded them according to the molecular interactions using the STRING database to find the drug target genes. Our analysis showed 27 biological AD risk genes, and they were mapped to 76 drug target genes. According to DrugBank and Therapeutic Target Database, 25 drug target genes overlapping with 53 drugs were identified. Importantly, dupilumab, which is approved for AD, was successfully identified in this bioinformatic analysis. Furthermore, ten drugs were found to be potentially useful for AD with clinical or preclinical evidence. In particular, we identified filgotinub and fedratinib, targeting gene JAK1, as potential drugs for AD. Furthermore, four monoclonal antibody drugs (lebrikizumab, tralokinumab, tocilizumab, and canakinumab) were successfully identified as promising for AD repurposing. In sum, the results showed the feasibility of gene networking and genomic information as a potential drug discovery resource.
Collapse
Affiliation(s)
- Wirawan Adikusuma
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Pharmacy, Faculty of Health Science, University of Muhammadiyah Mataram, Mataram, Indonesia
| | - Lalu Muhammad Irham
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Faculty of Pharmacy, University of Ahmad Dahlan, Yogyakarta, Indonesia
| | - Wan-Hsuan Chou
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
| | - Henry Sung-Ching Wong
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
| | - Eko Mugiyanto
- Ph. D. Program in the Clinical Drug Development of Herbal Medicines, College of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Pharmacy, Faculty of Health Science, University of Muhammadiyah Pekajangan Pekalongan, Pekalongan, Indonesia
| | - Jafit Ting
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
| | | | - Wei-Pin Chang
- School of Health Care Administration, College of Management, Taipei Medical University, Taipei, Taiwan
| | - Wei-Chiao Chang
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Taipei Medical University (TMU) Research Center of Cancer Translational Medicine, Taipei, Taiwan
- Department of Pharmacy, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
- Integrative Research Center for Critical Care, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
- Department of Pharmacology, National Defense Medical Center, Taipei, Taiwan
| |
Collapse
|
18
|
Irham LM, Chou WH, Calkins MJ, Adikusuma W, Hsieh SL, Chang WC. Genetic variants that influence SARS-CoV-2 receptor TMPRSS2 expression among population cohorts from multiple continents. Biochem Biophys Res Commun 2020; 529:263-269. [PMID: 32703421 PMCID: PMC7831678 DOI: 10.1016/j.bbrc.2020.05.179] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 05/25/2020] [Indexed: 02/07/2023]
Abstract
The World Health Organization recently announced that pandemic status has been achieved for coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Exponential increases in patient numbers have been reported around the world, along with proportional increases in the number of COVID-19-related deaths. The SARS-CoV-2 infection rate in a population is expected to be influenced by social practices, availability of vaccines or prophylactics, and the prevalence of susceptibility genes in the population. Previous work revealed that cellular uptake of SARS-CoV-2 requires Angiotensin Converting Enzyme 2 (ACE-2) and a cellular protease. The spike (S) protein on SARS-CoV-2 binds ACE-2, which functions as an entry receptor. Following receptor binding, transmembrane protease serine 2 (encoded by TMPRSS2) primes the S protein to allow cellular uptake. Therefore, individual expression of TMPRSS2 may be a crucial determinant of SARS-CoV-2 infection susceptibility. Here, we utilized multiple large genome databases, including the GTEx portal, SNP nexus, and Ensembl genome project, to identify gene expression profiles for TMPRSS2 and its important expression quantitative trait loci. Our results show that four variants (rs464397, rs469390, rs2070788 and rs383510) affect expression of TMPRSS2 in lung tissue. The allele frequency of each variant was then assessed in regional populations, including African, American, European, and three Asian cohorts (China, Japan and Taiwan). Interestingly, our data shows that TMPRSS2-upregulating variants are at higher frequencies in European and American populations than in the Asian populations, which implies that these populations might be relatively susceptible to SARS-CoV-2 infection.
Collapse
Affiliation(s)
- Lalu Muhammad Irham
- Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, 11031, Taiwan; Faculty of Pharmacy, University of Ahmad Dahlan, Yogyakarta, 55164, Indonesia
| | - Wan-Hsuan Chou
- Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, 11031, Taiwan; Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, School of Pharmacy, Taipei Medical University, Taipei, 11031, Taiwan
| | - Marcus J Calkins
- Institute of Cellular and Organismic Biology, Academia Sincia, Taipei, 11529, Taiwan
| | - Wirawan Adikusuma
- Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, 11031, Taiwan
| | - Shie-Liang Hsieh
- Genomics Research Center, Academia Sinica, Taipei, 11529, Taiwan
| | - Wei-Chiao Chang
- Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, 11031, Taiwan; Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, School of Pharmacy, Taipei Medical University, Taipei, 11031, Taiwan; Integrative Research Center for Critical Care, Wan Fang Hospital, Taipei Medical University-Taipei, 11696, Taiwan; Department of Medical Research, Shuang Ho Hospital, Taipei Medical University, New Taipei City, 23561, Taiwan.
| |
Collapse
|
19
|
Adikusuma W, Nopitasari BL. The Effect of Outcome Therapy to the Quality of Life Type 2 Diabetes Mellitus Patient on West Nusa Tenggara Hospital, Indonesia. J Young Pharm 2019. [DOI: 10.5530/jyp.2019.11.59] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
|
20
|
Adikusuma W, Qiyaam N. The Effect of Education through Short Message Service (SMS) Messages on Diabetic Patients Adherence. Sci Pharm 2017; 85:E23. [PMID: 28545222 PMCID: PMC5489927 DOI: 10.3390/scipharm85020023] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Revised: 04/27/2017] [Accepted: 05/03/2017] [Indexed: 01/23/2023] Open
Abstract
Poor adherence and a lack of understanding of medication instructions for oral antidiabetic use are key factors that inhibit the control of glycemic levels. The aforementioned situation needs intervention to improve medication adherence and the therapy. This study was conducted with a quasi-experimental design with prospective data collection. The subjects of this study were 50 outpatients with type 2 diabetes melitus (T2DM) who had received oral antidiabetic medicine therapy at least six months prior to adherence measurement. The patients were classified into two groups-the control group and the intervention group. The intervention group received Short Message Service (SMS) messages of diabetes education, while the control group did not. Data collection was conducted by doing interviews and administering the Morisky Medication Adherence Scale (MMAS) questionnaire. The results showed the increase in adherence in the intervention group as 1.15 ± 1.04 and that in the control group as 0.72 ± 0.90. These results indicated that there were significant differences in MMAS score between the control and intervention groups (p < 0.05). The decrease in fasting blood glucose and glucose measured 2 h postprandially was greater in the intervention group than that in the control group. It was concluded that the provision of education through SMS had a positive effect on medication adherence and glycemic levels.
Collapse
Affiliation(s)
- Wirawan Adikusuma
- Faculty of Health Science, University of Muhammadiyah Mataram, Mataram 83127, Indonesia.
| | - Nurul Qiyaam
- Faculty of Health Science, University of Muhammadiyah Mataram, Mataram 83127, Indonesia.
| |
Collapse
|